{"id":"W4412948483","doi":"10.1007/978-3-031-87031-6_1","title":"Introduction","year":2025,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on technology and health","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009794137,0.0008666716,0.0005349233,0.001488834,0.001313798,0.003869957,0.001610948,0.001809793,0.6759622],"category_scores_gemma":[0.003230213,0.00027618,0.0005737282,0.001106944,0.0004588188,0.002213486,0.002508621,0.001816667,0.5535478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552653,"about_ca_system_score_gemma":0.002610999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002987701,"about_ca_topic_score_gemma":0.005292616,"domain_scores_codex":[0.9991558,0.0001069142,0.0000284423,0.0001710328,0.0004469184,0.00009093511],"domain_scores_gemma":[0.998839,0.0001599338,0.00003512935,0.0001396795,0.0005815498,0.0002448113],"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":[0.00002229648,0.00002732288,0.00006344381,0.0001078454,0.000001525095,0.00002870864,0.00006027719,0.00006134249,0.0001930239,0.01296456,0.8704172,0.1160526],"study_design_scores_gemma":[0.000002742646,0.000006328756,0.00007061217,0.00005882552,8.546012e-7,0.00001867859,0.00003631346,0.00001782077,0.00005946703,0.002389498,0.9973368,0.000002174869],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003752381,0.00191965,0.004286574,0.005618779,0.009396161,0.0002325885,0.00393463,0.001072534,0.9731638],"genre_scores_gemma":[0.0009879851,0.0008869338,0.001453857,0.001787429,0.0008947481,0.0001205648,0.002232577,0.0002518682,0.991384],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3240378,"threshold_uncertainty_score":0.4622006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02085535706050954,"score_gpt":0.3259462896604052,"score_spread":0.3050909325998957,"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."}}