{"id":"W1595332999","doi":"","title":"Removing Barriers: Women in Academic Science, Technology, Engineering and Mathematics","year":2008,"lang":"en","type":"article","venue":"Canadian women's studies","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Science and engineering; Women in science; Mathematics education; Engineering ethics; Computer science; Engineering physics; Engineering; Mathematics; Sociology; Gender studies","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006631409,0.0004476588,0.001036979,0.002247731,0.04344436,0.008569043,0.002870198,0.003846046,0.00880062],"category_scores_gemma":[0.01484277,0.0004463354,0.0005467039,0.005608095,0.01419766,0.004635879,0.01076126,0.00560831,0.0003399512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05436554,"about_ca_system_score_gemma":0.1651227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9712898,"about_ca_topic_score_gemma":0.988321,"domain_scores_codex":[0.9889382,0.002062259,0.000141134,0.0004214442,0.001563296,0.00687364],"domain_scores_gemma":[0.9896783,0.002242331,0.000732934,0.0001909544,0.001506275,0.005649283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002679617,0.0002211555,0.05307475,0.0002665092,0.00003682197,0.0006042752,0.7711034,0.0001688261,0.0006276583,0.07906729,0.03250531,0.06205605],"study_design_scores_gemma":[0.00004152346,0.0000453328,0.07440639,0.0005079217,0.00004452595,0.00009197283,0.8381622,0.0001038573,0.0002162963,0.006595809,0.07973105,0.00005317936],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7895054,0.007552414,0.000573475,0.1229859,0.0007533512,0.0000952594,0.0002994806,0.00002333348,0.07821151],"genre_scores_gemma":[0.9805908,0.002156178,0.0002800906,0.006049076,0.0000631455,0.00004810215,0.00006043242,0.00001978518,0.01073244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05436554,"threshold_uncertainty_score":0.3944514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06138443772026291,"score_gpt":0.2791873665066132,"score_spread":0.2178029287863503,"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."}}