{"id":"W4417474102","doi":"10.1001/jamaoncol.2025.5376","title":"Enhancing Clinical Cancer Research Through Sharing of Data and Biospecimens","year":2025,"lang":"en","type":"article","venue":"JAMA Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Structural Genomics Consortium; Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Data sharing; Clinical trial; Quality (philosophy); MEDLINE; Patient data; Stakeholder; Data quality; Stakeholder engagement","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.6430815,0.001617704,0.004109047,0.009614418,0.005163279,0.02178927,0.01129624,0.01157181,0.01253432],"category_scores_gemma":[0.7605795,0.002869357,0.005262225,0.01144346,0.02039346,0.0387778,0.06435832,0.0144969,0.004818146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01105235,"about_ca_system_score_gemma":0.0913276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00243771,"about_ca_topic_score_gemma":0.002494416,"domain_scores_codex":[0.141476,0.7659516,0.04179571,0.01483255,0.03246324,0.003481064],"domain_scores_gemma":[0.0667839,0.7006176,0.06095267,0.1326599,0.02820162,0.01078439],"domain_codex":"methods","domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001712045,0.0006444447,0.02417673,0.02831806,0.003012238,0.0005886499,0.01067683,0.004039141,0.001483993,0.1321537,0.05067223,0.7425219],"study_design_scores_gemma":[0.002325417,0.002608298,0.01878755,0.07377083,0.001650658,0.001394633,0.009653239,0.003068574,0.003271698,0.2555924,0.6273667,0.0005099455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.01906506,0.09766735,0.2712951,0.5172033,0.008375237,0.02031356,0.003334767,0.001114777,0.06163091],"genre_scores_gemma":[0.2774526,0.05250451,0.4642415,0.138061,0.0125359,0.0436345,0.00439085,0.0007646897,0.006414351],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9887038,"threshold_uncertainty_score":0.4401441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1394081909485796,"score_gpt":0.5028676831765788,"score_spread":0.3634594922279992,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}