{"id":"W2891267781","doi":"10.23889/ijpds.v3i4.922","title":"Mapping Clinical Contents onto Longitudinal Depictions of Cross-Continuum Service Events in Island Health: Clinical Context Coding Scheme","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Island Health; University of British Columbia","funders":"","keywords":"Computer science; Coding (social sciences); Software deployment; Data science; Image stitching; Service (business); Context (archaeology); Software engineering; Artificial intelligence; Business; Geography; Marketing; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.002728684,0.0002607099,0.0001321145,0.004428925,0.000852574,0.003058803,0.0006071867,0.0004615944,0.00847193],"category_scores_gemma":[0.01250493,0.0002149628,0.0002902978,0.005346833,0.00108997,0.002587581,0.003041811,0.0007008611,0.001158717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002481184,"about_ca_system_score_gemma":0.003424266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03490068,"about_ca_topic_score_gemma":0.04606419,"domain_scores_codex":[0.9985558,0.0006747476,0.0002004692,0.0001835583,0.0002586218,0.0001266793],"domain_scores_gemma":[0.9938222,0.002385313,0.0008257217,0.001214571,0.001414473,0.0003376956],"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":[0.000638253,0.0001133575,0.2675774,0.001454479,0.00006789194,0.0009003824,0.07596113,0.008833267,0.01393663,0.1831752,0.06667013,0.3806719],"study_design_scores_gemma":[0.00007504735,0.0002560142,0.2560154,0.001971206,0.0001023353,0.001166663,0.1094644,0.0473255,0.01373405,0.05294913,0.5166969,0.0002432712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5976213,0.001191097,0.2211494,0.01065773,0.0003619982,0.002373333,0.06768332,0.004131741,0.09483007],"genre_scores_gemma":[0.6964868,0.0005432081,0.2815874,0.00033099,0.00003354257,0.001060565,0.01445942,0.0002022214,0.005295807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03490068,"threshold_uncertainty_score":0.06939512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.326119958882425,"score_gpt":0.5149831215027734,"score_spread":0.1888631626203484,"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."}}