{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004567184,0.0004663757,0.0002656757,0.0006566306,0.00342817,0.003758585,0.001210419,0.00124657,0.01217538],"category_scores_gemma":[0.01742852,0.0002248091,0.0002694642,0.0003851086,0.001872112,0.002591152,0.00595182,0.001884403,0.00149602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008182828,"about_ca_system_score_gemma":0.002839369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002192788,"about_ca_topic_score_gemma":0.006953028,"domain_scores_codex":[0.9974864,0.001295972,0.0000533894,0.000209677,0.0006243713,0.0003302041],"domain_scores_gemma":[0.9891441,0.005811581,0.001252651,0.001097132,0.0007503945,0.001944075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001500653,0.0034326,0.09443677,0.000474556,0.0001464486,0.0006611365,0.1157457,0.002053896,0.01214357,0.0299286,0.06126412,0.6782119],"study_design_scores_gemma":[0.0005340191,0.006066802,0.09585147,0.0008856105,0.0008173988,0.0008874531,0.3728977,0.01170231,0.02281648,0.07280753,0.4145247,0.0002085929],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9080827,0.0005540121,0.009864732,0.01508733,0.0005514029,0.0002007729,0.0001346614,0.000816728,0.06470761],"genre_scores_gemma":[0.9771017,0.0002360192,0.005597706,0.001619849,0.0001481401,0.0001479735,0.00007974931,0.00008758564,0.01498125],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01217538,"threshold_uncertainty_score":0.04073071,"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."}}