{"id":"W2954872693","doi":"","title":"Amplify: Managing Microaggressions and Countering Stereotypes against Women and Girls in STEM","year":2019,"lang":"en","type":"article","venue":"2019 ASTC Annual Conference (September 21 - 24)","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Science Centre","funders":"","keywords":"Psychology; Internet privacy; Gender studies; Social psychology; Political science; Sociology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005194343,0.0001722991,0.0002678656,0.0001438938,0.0002433063,0.0002615587,0.0002153202,0.0001175686,0.000427135],"category_scores_gemma":[0.00001568364,0.0001731466,0.0000219036,0.0001552355,0.0001928645,0.0006460845,0.0003348386,0.0001924851,0.0002038028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001282243,"about_ca_system_score_gemma":0.0001692444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005933509,"about_ca_topic_score_gemma":0.001132161,"domain_scores_codex":[0.9985583,0.0001052548,0.0001906719,0.0003901447,0.0002797547,0.0004758083],"domain_scores_gemma":[0.9993686,0.00009066195,0.00009053289,0.0001491604,0.0001124527,0.0001885606],"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":[0.00007011832,0.00003262918,0.8613085,0.00007221332,0.00003587362,0.00001631548,0.1101817,0.000002964227,0.0002889828,0.001408563,0.007063942,0.01951819],"study_design_scores_gemma":[0.002277529,0.0001142739,0.3398995,0.0006977533,0.00002181694,0.000005556347,0.2450218,0.0001883559,0.00005556722,0.0008269234,0.4096655,0.001225493],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9614048,0.0002170239,0.00001909896,0.0002881208,0.0004353312,0.0002846325,0.00004719054,0.00004808444,0.03725574],"genre_scores_gemma":[0.9770815,0.0002561551,0.00008970225,0.000206232,0.00004780773,0.000007152349,0.00001025403,0.000009909443,0.02229133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.521409,"threshold_uncertainty_score":0.7060714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942781370391568,"score_gpt":0.2546743200530017,"score_spread":0.235246506349086,"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."}}