{"id":"W2154132674","doi":"","title":"Inspiring Girls and their Female After School Educators to Pursue Computer Science and other STEM Careers","year":2012,"lang":"en","type":"article","venue":"International Journal of Gender, Science, and Technology","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Women in science; Science education; Medical education; Psychology; Mathematics education; Political science; Sociology; Medicine; Gender studies","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002686862,0.000355178,0.0004400518,0.000867811,0.008666309,0.004772517,0.0006379812,0.001177555,0.006731235],"category_scores_gemma":[0.003525869,0.000303337,0.0003805019,0.0005469819,0.002450599,0.001606288,0.003858421,0.002366788,0.0007423586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001703245,"about_ca_system_score_gemma":0.003164723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008900163,"about_ca_topic_score_gemma":0.0310734,"domain_scores_codex":[0.9984148,0.0005918313,0.00003111838,0.0001513145,0.0002576046,0.0005534159],"domain_scores_gemma":[0.9968621,0.0005462603,0.0005485648,0.0001006188,0.000341029,0.001601438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001457782,0.001069315,0.2674279,0.0001635887,0.00002963343,0.001695256,0.6103014,0.00004654067,0.003888256,0.007145894,0.01733078,0.09075578],"study_design_scores_gemma":[0.00003204105,0.0003581311,0.07455947,0.0001825911,0.00002063925,0.0006619167,0.8302324,0.00004318503,0.00104263,0.001325052,0.09150941,0.00003248754],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780039,0.0006020305,0.0003444044,0.006286053,0.0002486274,0.00007665787,0.00007752023,0.00001671862,0.01434406],"genre_scores_gemma":[0.9818793,0.0007080656,0.0006077055,0.002827855,0.00006944832,0.00007572302,0.00005842784,0.00002281091,0.01375072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008900163,"threshold_uncertainty_score":0.02251828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693169698020324,"score_gpt":0.2887791396843251,"score_spread":0.2618474427041219,"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."}}