{"id":"W4281851534","doi":"10.1158/2159-8290.cd-22-0330","title":"REFLECTions on Combination Therapies Empowered by Data Sharing","year":2022,"lang":"en","type":"letter","venue":"Cancer Discovery","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Vector Institute; Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Canada Research Chairs","keywords":"Compendium; Data sharing; Clinical trial; Precision oncology; Computational biology; Transcriptome; Drug approval; Drug discovery; Precision medicine; Medicine; MEDLINE; Bioinformatics; Computer science; Data science; Pharmacology; Drug; Biology; Alternative medicine; Genetics; Pathology; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009361184,0.0002563614,0.0001978589,0.00005891466,0.0001941113,0.0001792066,0.0009391009,0.0002914332,0.0002279829],"category_scores_gemma":[0.00004007112,0.0002762844,0.00008925068,0.00008726012,0.00005626436,0.00001159832,0.0007271158,0.0005885168,0.000005428126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001792979,"about_ca_system_score_gemma":0.0002461729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003026606,"about_ca_topic_score_gemma":0.0001439018,"domain_scores_codex":[0.9983718,0.00003736513,0.0002012314,0.0009093993,0.0002141606,0.0002659993],"domain_scores_gemma":[0.9982928,0.00003287388,0.0001589804,0.001452382,0.0000338968,0.00002905106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005599979,0.00004097758,0.00007946705,0.00002923309,0.0001630224,0.000007079194,0.00002760348,0.00006173777,0.006775768,0.00005354488,0.992281,0.0004246358],"study_design_scores_gemma":[0.0003418755,0.000219664,0.00003615194,0.00002730288,0.00005416593,0.000002292443,0.00003628221,0.00001125035,0.001964149,0.0001920467,0.9967737,0.0003411097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.03843279,0.05710651,0.001583028,0.7967513,0.01580169,0.001866137,0.06128826,0.0001258418,0.02704448],"genre_scores_gemma":[0.02796046,0.02186514,0.00004936603,0.819065,0.007791962,0.0005913185,0.09489647,0.0002424696,0.02753783],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03524137,"threshold_uncertainty_score":0.9999689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05162716659467738,"score_gpt":0.3414896131805871,"score_spread":0.2898624465859097,"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."}}