{"id":"W7024245410","doi":"","title":"Reaching out: A look at initiatives – old and new – to increase diversity in Canadian law schools.","year":2020,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Diversity (politics); Legislation; Government (linguistics); Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002524875,0.0002614774,0.0003636306,0.0001002175,0.0002480186,0.00005241834,0.0003156355,0.0001394708,0.0001515269],"category_scores_gemma":[0.0006803875,0.0002817693,0.00007780263,0.0002835506,0.00003917612,0.0006162283,0.0008194098,0.0006272976,0.0003702508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000855089,"about_ca_system_score_gemma":0.0001293986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8187755,"about_ca_topic_score_gemma":0.7561884,"domain_scores_codex":[0.9983004,0.00004366773,0.0002818388,0.0004884896,0.000251431,0.0006342072],"domain_scores_gemma":[0.9971145,0.00007468805,0.00005138798,0.0002928431,0.00002612832,0.002440398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001052517,0.0001684913,0.3405186,0.001086196,0.0006386373,0.002675226,0.04007743,0.001878874,0.305936,0.2963426,0.003908101,0.005717315],"study_design_scores_gemma":[0.01600656,0.0006057257,0.03385533,0.002371785,0.0005116278,0.0002318367,0.003929023,0.005989668,0.3225613,0.003962696,0.602727,0.007247448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973178,0.0002669079,0.00004503634,0.001517685,0.0000795395,0.0002812089,0.00006644528,0.0001475635,0.02441758],"genre_scores_gemma":[0.9947312,0.0000116669,0.000587573,0.003667222,0.0002174533,0.000008172155,0.00003811132,0.00004219215,0.0006963966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5988189,"threshold_uncertainty_score":0.9999635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02509566532896289,"score_gpt":0.2404399976579282,"score_spread":0.2153443323289653,"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."}}