{"id":"W4401034543","doi":"10.1177/14604582241267792","title":"A novel technology for harmonizing and analyzing cancer data. Observations from integrating health connect in Newfoundland and Labrador, Canada","year":2024,"lang":"en","type":"article","venue":"Health Informatics Journal","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Newfoundland and Labrador Centre for Applied Health Research","funders":"","keywords":"Cancer; Health data; Data science; Computer science; Geography; Knowledge management; Health care; Medicine; Political science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005539975,0.000590611,0.0003430522,0.003820544,0.002658503,0.002900255,0.001147549,0.0004423412,0.002599706],"category_scores_gemma":[0.01272632,0.0004353804,0.0006934601,0.01101428,0.001292649,0.001434966,0.002681169,0.0006818037,0.0005420209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02866452,"about_ca_system_score_gemma":0.0444096,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9659144,"about_ca_topic_score_gemma":0.9752695,"domain_scores_codex":[0.9945191,0.0009118805,0.0004071819,0.0009735853,0.00263198,0.0005563223],"domain_scores_gemma":[0.990639,0.001980598,0.0008655049,0.001548001,0.004387525,0.0005794011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008852981,0.0001909045,0.3149122,0.0008093028,0.0004863109,0.000689626,0.006446752,0.0164225,0.01227963,0.02560802,0.1561132,0.4651562],"study_design_scores_gemma":[0.0001751885,0.0001968054,0.3938725,0.0004082346,0.0003820138,0.0006069351,0.008027691,0.04086429,0.01596522,0.008544345,0.5307434,0.0002134148],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4173348,0.004943531,0.239109,0.04349502,0.0005195853,0.002713117,0.1362367,0.0179093,0.1377391],"genre_scores_gemma":[0.6139934,0.002459485,0.2861711,0.003482673,0.0001343498,0.0007315754,0.0677828,0.0008529922,0.02439157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03408563,"threshold_uncertainty_score":0.2079766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048003655327648,"score_gpt":0.3553497999984447,"score_spread":0.2505494344656798,"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."}}