{"id":"W6958360683","doi":"10.6084/m9.figshare.14060073.v1","title":"Additional file 1 of Capturing the impact of cultural differences in residency","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; University of Ottawa","funders":"","keywords":"Cultural diversity; Variation (astronomy); Statistical analysis; Data collection","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":[],"category_scores_codex":[0.002050248,0.0008274591,0.0009155811,0.002522283,0.00093825,0.001546863,0.001536607,0.001055547,0.8347687],"category_scores_gemma":[0.04250371,0.0005195601,0.0008417912,0.005011661,0.0002811865,0.002044397,0.001147392,0.001093049,0.1426407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008935989,"about_ca_system_score_gemma":0.001986903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02544078,"about_ca_topic_score_gemma":0.03235102,"domain_scores_codex":[0.9989997,0.0002854828,0.0001487157,0.0002174052,0.0001882626,0.0001603889],"domain_scores_gemma":[0.9663599,0.02685236,0.001532366,0.001539391,0.003022459,0.0006934261],"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":[0.0001315963,0.00005309179,0.005135197,0.001210702,0.00003985123,0.00003547695,0.0001047259,0.0004058593,0.00003230952,0.0008841217,0.9871557,0.004811365],"study_design_scores_gemma":[0.003644649,0.0002595109,0.086493,0.003813454,0.0003131156,0.0004476723,0.001793465,0.002699407,0.0005602079,0.01372801,0.8860753,0.0001723219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002718206,0.00001412237,0.0002039315,0.00008391093,0.0000136679,0.00005900348,0.9981831,0.0001016979,0.001068723],"genre_scores_gemma":[0.01865687,0.000154327,0.003847723,0.0005979314,0.00008927711,0.003135072,0.9531384,0.0009415321,0.0194389],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8347687,"threshold_uncertainty_score":0.2356824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05071006775347684,"score_gpt":0.2220620962562636,"score_spread":0.1713520285027867,"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."}}