{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29393370", "kind": "science-record", "revision": 4, "content_hash": "sha256:5fa877ce509296b2a551097c25eb4e7e197a65f726c9247e16d052460cfbbf48", "created_at": "2026-11-01T15:40:31Z", "updated_at": "2026-11-01T21:21:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 63 signature genes prediction system is effective for glioblastoma prognosis.", "doi": "10.3892/ijmm.2018.3422", "pmid": "29393370", "authors": ["Yang Zhang", "Jiaming Xu", "Xiangdong Zhu"], "journal": "International journal of molecular medicine", "year": 2018, "abstract": "The present study aimed to explore possible prognostic marker genes in glioblastoma (GBM). Differentially expressed genes (DEGs) were screened by comparing microarray data of tumor and normal tissue samples from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset GSE22866. Subsequently, the prognosis‑associated DEGs were screened via Cox regression analysis, followed by construction of gene/protein/pathway interaction networks of these DEGs by calculating the correlation coefficient between the DEGs. Next, a prognostic prediction system was constructed using Bayes discriminant analysis, which was validated by the microarray data of samples from patients with good and bad prognosis from the TCGA and Chinese Glioma Genome Atlas (CGGA), as well as the GEO dataset. Finally, a co‑expression network of the signature genes in the prediction system was constructed in combination with the significant pathways. A total of 288 overlapping DEGs (false discovery rate <0.5 and |log2 of fold change|>1) were screened, 123 of which were identified to be associated with the prognosis of GBM patients. The co‑expression network of these prognosis‑associated DEGs included 1405 interactions and 112 DEGs, and 6 functional modules were identified in the network. The prognostic prediction system was comprised of 63 signature genes with a specificity value of 0.929 and a sensitivity value of 0.948. GBM samples with good and bad prognosis in the TCGA, CGGA and GEO datasets were distinguishable by these signature genes (P=1.33x10‑6, 1.63x10‑4 and 0.00534, respectively). The co‑expression network of signature genes with significant pathways was comprised of 56 genes and 361 interactions. Protein kinase Cγ (PRKCG), protein kinase Cβ (PRKCB) and calcium/calmodulin‑dependent protein kinase IIα (CAMK2A) were important genes in the network, and based on the expression of these genes, it was possible to distinguish between samples with significantly different survival risks. In the present study, an effective prognostic prediction system for GBM patients was constructed and validated. PRKCG, PRKCB and CAMK2A may be potential prognostic factors for GBM.", "claims": [{"id": "claim-method", "statement": "Based on the co-expression network of prognosis-associated genes, a prognostic prediction system comprising 63 signature genes was constructed using Bayes discriminant analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29393370", "locator": "sections[15] \"Construction of prognostic prediction system\" paragraph 2", "quote": "Based on the co-expression network of prognosis-associated genes, a prognostic prediction system comprising 63 signature genes was constructed using Bayes discriminant analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mRNA expression data for GBM were downloaded from TCGA database (https://gdc-portal.nci.nih.gov/) on 25th Dec 2016, including 154 tumor samples (survival time information was available for 152 samples) and 13 normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29393370", "locator": "sections[3] \"Microarray data\" paragraph 2", "quote": "The mRNA expression data for GBM were downloaded from TCGA database (https://gdc-portal.nci.nih.gov/) on 25th Dec 2016, including 154 tumor samples (survival time information was available for 152 samples) and 13 normal samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An effective prognostic prediction system for GBM patients was constructed and validated using Cox regression, Kaplan-Meier survival analysis, correlation-based co-expression networks, Bayes discriminant analysis, and ROC analysis of TCGA data with validation in GSE13041 and CGGA data.", "kind": "quantitative", "target": {"value": 3.4, "unit": "correlation coefficient", "tolerance": null, "source": "The effectiveness of the prognostic prediction system was evaluated by the receiver operating characteristic (ROC) curve using the pROC package in R3.4.1 (https://cran.r-project.org/web/packages/pROC/index.html)."}, "evidence": [{"asset": "source:pmid:29393370", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In the present study, an effective prognostic prediction system for GBM patients was constructed and validated."}, {"asset": "source:pmid:29393370", "locator": "sections[5] \"Identification of prognosis-associated DEGs\" paragraph 2", "quote": "Cox regression analysis in the survival package (13) was utilized to select the prognosis-associated genes from the overlapping DEGs, based on the expression values and survival status data."}, {"asset": "source:pmid:29393370", "locator": "sections[7] \"Construction of a prognostic prediction system\" paragraph 2", "quote": "Based on this grouping, Bayes discriminant analysis was performed to analyze the genes in the co-expression network constructed for the prognosis-associated DEGs by using the discriminant Bayes function in R language (15,16)."}, {"asset": "source:pmid:29393370", "locator": "sections[7] \"Construction of a prognostic prediction system\" paragraph 2", "quote": "The effectiveness of the prognostic prediction system was evaluated by the receiver operating characteristic (ROC) curve using the pROC package in R3.4.1 (https://cran.r-project.org/web/packages/pROC/index.html)."}, {"asset": "source:pmid:29393370", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The prognostic prediction system was comprised of 63 signature genes with a specificity value of 0.929 and a sensitivity value of 0.948."}, {"asset": "source:pmid:29393370", "locator": "sections[16] \"Validation of the prognostic prediction system\" paragraph 2", "quote": "In order to validate the performance of the prognostic prediction system, it was tested on the GEO GSE13041 and CGGA datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An effective prognostic prediction system for GBM patients was constructed and validated using Cox regression, Kaplan-Meier survival analysis, correlation-based co-expression networks, Bayes discriminant analysis, and ROC analysis of TCGA data with validation in GSE13041 and CGGA data.", "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:29393370"], "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. 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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":"2026-11-04T02:12:37+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}}}