{"id":"W2329950980","doi":"","title":"RECODING GENDER: WOMEN’S CHANGING PARTICIPATION IN COMPUTING","year":2016,"lang":"en","type":"article","venue":"Alternate routes","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008634136,0.00005322568,0.00006988205,0.0001746734,0.0001881732,0.00002592076,0.0001357282,0.00005154736,0.0000753186],"category_scores_gemma":[0.0001759175,0.00004431575,0.00001518332,0.0002030184,0.0000507806,0.0001716736,0.00003279265,0.00004865174,0.00005534116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002739958,"about_ca_system_score_gemma":0.00003322748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003299874,"about_ca_topic_score_gemma":0.0002822493,"domain_scores_codex":[0.9991063,0.00009251265,0.0001327496,0.0001501961,0.0001088994,0.0004092761],"domain_scores_gemma":[0.9996766,0.0001101331,0.00005811054,0.00008823897,0.00002485295,0.00004206389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002504929,0.00004845977,0.5736891,0.00000539393,0.0000127605,0.000003196359,0.1219133,0.00001079429,0.001268026,0.03994805,0.00003879384,0.2630596],"study_design_scores_gemma":[0.002234255,0.000113729,0.5324043,0.0003502658,0.00002782606,0.000006770197,0.15852,0.001300656,0.01801953,0.2721071,0.01377788,0.001137735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891282,0.00003961732,0.001876423,0.002031229,0.0005658287,0.00007660248,5.176437e-7,0.0001120132,0.006169549],"genre_scores_gemma":[0.9990793,0.00007876741,0.0002199196,0.00007601648,0.0001835029,0.00002245797,5.637754e-7,0.000005760246,0.0003337445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2619219,"threshold_uncertainty_score":0.1807144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04659608262492139,"score_gpt":0.3529797934206664,"score_spread":0.3063837107957451,"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."}}