{"id":"W3038981544","doi":"10.7554/elife.60438","title":"Ways to increase equity, diversity and inclusion","year":2020,"lang":"en","type":"article","venue":"eLife","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Alberta","funders":"","keywords":"Equity (law); Diversity (politics); Inclusion (mineral); Racism; Public relations; Political science; Sociology; Social science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.009669363,0.00007619157,0.0001649674,0.009437956,0.002393263,0.0005458492,0.001909368,0.00004887007,0.0003634096],"category_scores_gemma":[0.0421023,0.00005438316,0.00004546357,0.07472676,0.00005609036,0.0002866526,0.1819475,0.0001283852,0.0005894367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003975817,"about_ca_system_score_gemma":0.0000507258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002659286,"about_ca_topic_score_gemma":0.00001279398,"domain_scores_codex":[0.9902923,0.00006425064,0.0002306837,0.0004952028,0.008612008,0.000305519],"domain_scores_gemma":[0.9964082,0.001121795,0.00005455976,0.0002814417,0.000869763,0.001264249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001240089,0.0001076109,0.4177611,0.000008550765,0.00001008254,0.00007615272,0.007301554,0.00002761648,0.003772895,0.004153583,0.2232361,0.3434207],"study_design_scores_gemma":[0.001394237,0.0009311709,0.5165017,0.00001084024,0.00001135162,0.00000643775,0.0006020128,0.01333158,0.004354495,0.03425431,0.4280497,0.0005522292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695554,0.0002364405,0.008179222,0.01156367,0.0001206509,0.000140896,0.00002307307,0.00002744579,0.01015313],"genre_scores_gemma":[0.9929178,0.00006510188,0.0008944634,0.005879851,0.00009456696,9.860858e-7,7.975916e-7,0.00000333093,0.0001431375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3428685,"threshold_uncertainty_score":0.9989055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7864795108863052,"score_gpt":0.5846512036689153,"score_spread":0.2018283072173899,"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."}}