{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36267782", "kind": "science-record", "revision": 4, "content_hash": "sha256:08db762fdd97ac6d408223affb4c4fe36a8d644985f29c62a0f922b152b34189", "created_at": "2026-11-01T18:15:40Z", "updated_at": "2026-11-01T22:50:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and verification of a glycolysis-related gene signature for gastric cancer.", "doi": "10.21037/atm-22-3980", "pmid": "36267782", "authors": ["Yi Liu", "Min Wu", "Jian Cao", "Yaning Zhu", "Yu Ma", "Yansong Pu", "Xueping Huo", "Jianhua Wang"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Glycolysis is a central metabolic pathway for tumor cells. However, the relationship between glycolysis and the prognosis of gastric cancer (GC) patients is not well established. In this study, we sought to construct a glycolysis-related gene signature for GC.\nMethods: The messenger ribonucleic acid (mRNA) expression profiles were analyzed using data from The Cancer Genome Atlas (TCGA) database. Glycolysis-related gene sets and pathways were obtained from the Molecular Signatures Database (MSigDB). Subsequently, a prognosis prediction model of the glycolysis-related genes was constructed using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. An external validation was conducted using data from the Gene Expression Omnibus (GEO) database. Risk scores were also calculated based on the signature. Finally, the correlations between the risk score and overall survival (OS), mutation, immune cell infiltration, immune score, and stromal score were examined in 22 types of infiltrating immune cells.\nResults: Fifty-five glycolysis-related genes were identified from TCGA database and MSigDB. Using the LASSO and Cox models, 4 novel genes (i.e., VCAN, EFNA3, ADH4, and CLDN9) were identified to construct a gene signature for GC prognosis prediction. The GC patients with low-risk scores had significantly better OS than those with high-risk scores in the training set. Similar results were also found in the independent GEO GSE84437 testing set. Additionally, the degree of cell infiltration in the low-risk group was significantly higher than that in the high-risk group in terms of naive B cells, plasma cells, and T follicular helper cells. In monocytes, M2 macrophages, resting dendritic cells, and resting Mast cells, the degree of infiltration in the high-risk group was significantly higher than that in the low-risk group. The immune score and stromal score of the high-risk group were also significantly higher than those of the low-risk group. Finally, the univariate and multivariate Cox regression analyses showed that 4 glycolysis-related genes were independent prognostic factors for GC.\nConclusions: The established 4 glycolysis-related gene signature may serve as a reliable tool for the prognosis of GC patients and provide a potential glycolysis therapeutic target for GC.", "claims": [{"id": "claim-method", "statement": "A univariate Cox regression analysis was performed to screen the glycolysis-related DEGs whose expression levels were closely related to the overall survival (OS) of the GC patients using the “survival” R package. Subsequently, we further used least absolute shrinkage and selection operator (LASSO) regression to identify glycolysis-related genes for the prognostic signature through the R package “glmnet” (22,23) according to the results of the univariate Cox regression analysis (P<0.05).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36267782", "locator": "sections[8] \"Construction and validation of the prognostic model of GC\" paragraph 2", "quote": "A univariate Cox regression analysis was performed to screen the glycolysis-related DEGs whose expression levels were closely related to the overall survival (OS) of the GC patients using the “survival” R package. Subsequently, we further used least absolute shrinkage and selection operator (LASSO) regression to identify glycolysis-related genes for the prognostic signature through the R package “glmnet” (22,23) according to the results of the univariate Cox regression analysis (P<0.05)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The clinical data and messenger ribonucleic acid (mRNA) expression profiles of GC were downloaded from The Cancer Genome Atlas (TCGA) database (https://xena.ucsc.edu/). In total, 350 GC samples and 31 normal control samples were obtained from TCGA database. The somatic mutation data of the GC samples were also downloaded from TCGA database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36267782", "locator": "sections[4] \"Tumor and clinical data collection\" paragraph 2", "quote": "The clinical data and messenger ribonucleic acid (mRNA) expression profiles of GC were downloaded from The Cancer Genome Atlas (TCGA) database (https://xena.ucsc.edu/). In total, 350 GC samples and 31 normal control samples were obtained from TCGA database. The somatic mutation data of the GC samples were also downloaded from TCGA database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using LASSO and Cox models, the study identified 4 glycolysis-related genes and constructed a gastric cancer prognostic signature.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36267782", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Using the LASSO and Cox models, 4 novel genes (i.e., VCAN, EFNA3, ADH4, and CLDN9) were identified to construct a gene signature for GC prognosis prediction."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using LASSO and Cox models, the study identified 4 glycolysis-related genes and constructed a gastric cancer prognostic signature.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36267782"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE84437"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE84437"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36267782", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/atm-22-3980", "sha256": "sha256:415ee406e012843b02ce81520ae5e21c13dd40e56ba0ae11d0b14740abe85fa8", "bytes": 39321, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/atm-22-3980", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9577805", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE84437", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84437", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE84437", "version": null, "note": "The clinical data and messenger ribonucleic acid (mRNA) expression profiles of GC were downloaded from The Cancer Genome Atlas (TCGA) database (https://xena.ucsc.edu/). In total, 350 GC samples and 31 normal control samples were obtained from TCGA database. The somatic mutation data of the GC samples were also downloaded from TCGA database.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The clinical data and messenger ribonucleic acid (mRNA) expression profiles of GC were downloaded from The Cancer Genome Atlas (TCGA) database (https://xena.ucsc.edu/). In total, 350 GC samples and 31 normal control samples were obtained from TCGA database. 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"group_sizes": null, "group_sizes_basis": null, "platform": "6947", "taxon": "Homo sapiens", "title": "Molecular subtypes in gastric cancer.", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE84437 not downloaded", "asset:data:geo:GSE84437 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "A univariate Cox regression analysis was performed to screen the glycolysis-related DEGs whose expression levels were closely related to the overall survival (OS) of the GC patients using the “survival” R package. Subsequently, we further used least absolute shrinkage and selection operator (LASSO) regression to identify glycolysis-related genes for the prognostic signature through the R package “glmnet” (22,23) according to the results of the univariate Cox regression analysis (P<0.05)."}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE84437"], "resolved_accessions": ["GSE84437"], "statements": ["The clinical data and messenger ribonucleic acid (mRNA) expression profiles of GC were downloaded from The Cancer Genome Atlas (TCGA) database (https://xena.ucsc.edu/). In total, 350 GC samples and 31 normal control samples were obtained from TCGA database. The somatic mutation data of the GC samples were also downloaded from TCGA database."], "basis": "The paper names GSE84437 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:36267782", "data:geo:GSE84437"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE84437"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:12:23Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 11848, "completion_tokens": 1502, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36267782", "type": "paper", "label": "pmid:36267782"}, {"id": "source:pmid:36267782", "type": "manuscript", "label": "PMID 36267782 full text"}, {"id": "data:geo:GSE84437", "type": "dataset", "label": "GEO GSE84437"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36267782", "type": "paper", "label": "pmid:36267782"}, {"id": "source:pmid:36267782", "type": "manuscript", "label": "PMID 36267782 full text"}, {"id": "data:geo:GSE84437", "type": "dataset", "label": "GEO GSE84437"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36267782", "type": "extraction", "used": ["source:pmid:36267782"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE84437", "type": "accession_resolution", "used": ["data:geo:GSE84437"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:36267782", "parent_hash": "sha256:1646028cd3235dec649d640873ddd86553ea9cafa0378556eaa903e3c959fe74", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE84437 licence not read", "asset:data:geo:GSE84437 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["A univariate Cox regression analysis was performed to screen the glycolysis-related DEGs whose expression levels were closely related to the overall survival (OS) of the GC patients using the “survival” R package. Subsequently, we further used least absolute shrinkage and selection operator (LASSO) regression to identify glycolysis-related genes for the prognostic signature through the R package “glmnet” (22,23) according to the results of the univariate Cox regression analysis (P<0.05)."], "order_basis": "analysis_only", "id": "assay:1"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T02:39:18+00:00","total_papers":5529,"total_assays_tracked":29,"automatable_assay_families":6,"validated":true,"caveat_count":9,"blocking_caveats":5,"caveats":[{"code":"low_evidence_dominates","basis":["4,152 of 5,529 classifications (75.1%) matched no cue evidence and sit at the 0.05 floor.","34 of 230 data_only calls (14.8%) are in that group."],"claim":"Work type and confidence bands","gloss":"Most records were classified from their title and framing alone, with assay-cue coverage at zero.","detail":"Most classifications in this run rest on no matched evidence at all. At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. Timing awaits the first executed replication.","4,407 of 5,529 records (79.7%) model to 0.00 hours because no assay was matched, which the ranking then reads as \"cheapest\".","0 of 10 shortlisted records carry a 0.00-hour estimate."],"claim":"Estimated replication runtime","gloss":"The hour figures are estimates built from assay mentions; timing awaits the first executed replication.","detail":"The hour figures are a cost model derived from the bench steps implied by each matched assay family. The first executed replication will supply measured timing. Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}