{"id":"W3087567625","doi":"10.1523/jneurosci.2285-20.2020","title":"Reporting Grantee Demographics for Diversity, Equity, and Inclusion in Neuroscience","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Redress; Equity (law); Diversity (politics); Inclusion (mineral); Demographics; Ethnic group; Political science; Public relations; Psychology; Sociology; Social psychology; Law","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1074373,0.000355673,0.0007124525,0.008763839,0.003734709,0.003631885,0.001381499,0.001112346,0.005966796],"category_scores_gemma":[0.2690618,0.0003318998,0.0007767151,0.00843681,0.001142527,0.004652126,0.005580981,0.001591553,0.002020368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002411785,"about_ca_system_score_gemma":0.01362266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005380027,"about_ca_topic_score_gemma":0.01138855,"domain_scores_codex":[0.9371359,0.02791848,0.01570603,0.002144907,0.01282973,0.004264933],"domain_scores_gemma":[0.7199034,0.06630857,0.09094865,0.02226964,0.0853117,0.01525797],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002574337,0.0001485488,0.7646495,0.0007057631,0.0001780444,0.0001368756,0.009868279,0.0002280791,0.001630987,0.00783421,0.09199575,0.1223667],"study_design_scores_gemma":[0.00007105502,0.0003036239,0.7342909,0.001592626,0.0001945275,0.0008666432,0.02588912,0.001819551,0.00324843,0.01828734,0.2132326,0.0002036723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7174585,0.007043472,0.05044663,0.09446105,0.003134107,0.009204427,0.03327499,0.001092467,0.08388443],"genre_scores_gemma":[0.9252344,0.004840431,0.03400966,0.00710487,0.001170038,0.01092101,0.009644855,0.000259523,0.0068152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8925627,"threshold_uncertainty_score":0.5681896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1884550512972946,"score_gpt":0.3862274124871049,"score_spread":0.1977723611898103,"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."}}