{"id":"W4387578221","doi":"10.12927/hcpol.2023.27186","title":"Appendix 1: Macro Policy Data Collection Template","year":2023,"lang":"fr","type":"article","venue":"Healthcare policy","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Macro; Computer science; Data collection; Data science; Statistics; Mathematics; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001518671,0.0003979121,0.0004616563,0.001348541,0.001959628,0.0001949014,0.001278425,0.0005378319,0.0004856008],"category_scores_gemma":[0.0008172791,0.0004550166,0.0001344167,0.01035578,0.0006509871,0.0006976072,0.0006769404,0.0005055782,0.02139201],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001475974,"about_ca_system_score_gemma":0.01026358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5387485,"about_ca_topic_score_gemma":0.02807714,"domain_scores_codex":[0.9946764,0.000859032,0.0006889591,0.0008374984,0.0009002332,0.002037952],"domain_scores_gemma":[0.9972681,0.0003568527,0.000283329,0.0009811474,0.0001850091,0.0009255585],"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":[0.00002091138,0.00003161472,0.002298471,0.0002299388,0.000042774,0.00002764543,0.01001261,0.000003319818,0.000003710073,0.3666283,0.5484709,0.07222986],"study_design_scores_gemma":[0.000327909,0.00006289306,0.01538889,0.000177287,0.00001397527,0.00003482279,0.0009313067,0.0003005015,0.000007277255,0.03518512,0.9471614,0.0004085971],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0110755,0.002864679,0.00001599184,0.9083096,0.003697177,0.0007948993,0.0008335426,0.0005273409,0.07188126],"genre_scores_gemma":[0.1667691,0.06484459,0.0004574482,0.02109252,0.02750225,0.00009254652,0.002597271,0.0001539616,0.7164903],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.8872171,"threshold_uncertainty_score":0.9997901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1922828702717202,"score_gpt":0.459619453912032,"score_spread":0.2673365836403118,"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."}}