{"id":"W4317863097","doi":"10.46747/cfp.690169","title":"Journey of reconciliation","year":2023,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Social Science and Policy Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of Family Physicians of Canada","funders":"","keywords":"Computer science; World Wide Web; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006549618,0.00004312036,0.00008560625,0.0002090541,0.0004874924,0.0000390415,0.0002622078,0.00005820658,0.00001533985],"category_scores_gemma":[0.0001145316,0.00004785002,0.00004974726,0.001704457,0.0002340881,0.0001592705,0.000009366237,0.00007421063,0.000583531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002365048,"about_ca_system_score_gemma":0.001852534,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3994947,"about_ca_topic_score_gemma":0.350533,"domain_scores_codex":[0.9988896,0.0001003704,0.00009552506,0.0001046678,0.0003278981,0.0004818971],"domain_scores_gemma":[0.9993041,0.00007500732,0.00003580825,0.0001014064,0.0001114146,0.0003723085],"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":[0.000004160651,0.0000156659,0.003823785,0.00001261589,0.0000237949,0.00001261143,0.03503219,0.00002472892,0.0036836,0.141368,0.5094418,0.3065571],"study_design_scores_gemma":[0.00008427509,0.00002050645,0.04404957,0.00001533812,0.000003442319,9.621523e-9,0.02715088,0.00004312436,0.0001550358,0.01192251,0.9164327,0.0001225845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2895591,0.00003101285,7.494959e-7,0.003676694,0.0002460243,0.0001094578,0.00002466815,0.00003543683,0.7063168],"genre_scores_gemma":[0.9844671,0.00009837838,0.000006542958,0.01147074,0.0005886086,0.000008176199,0.0000081848,0.000007021082,0.003345223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7029716,"threshold_uncertainty_score":0.7500305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1325676765293673,"score_gpt":0.391567797021613,"score_spread":0.2590001204922457,"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."}}