{"id":"W2785182746","doi":"","title":"The Access Program for Women in Science and Engineering (ACCESS W.I.S.E.)","year":2006,"lang":"en","type":"article","venue":"Women in Engineering ProActive Network","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Science and engineering; Women in science; Engineering; Engineering management; Library science; Engineering physics; Engineering ethics; Telecommunications; Computer science; Sociology; Gender studies","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006909354,0.0004156076,0.000371565,0.001258557,0.0008236902,0.0009009843,0.0005163879,0.0009315104,0.4142643],"category_scores_gemma":[0.002208513,0.0001351449,0.0002155282,0.0007441651,0.0002407161,0.001026176,0.002890131,0.0007162863,0.07971636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003774911,"about_ca_system_score_gemma":0.001995978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003411493,"about_ca_topic_score_gemma":0.008741614,"domain_scores_codex":[0.9997584,0.00004305733,0.000006288219,0.00003877816,0.00006743408,0.0000859293],"domain_scores_gemma":[0.9983615,0.0002025282,0.0000766985,0.00006683659,0.0001397149,0.001152693],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002339448,0.0002704237,0.001845165,0.0001138605,0.000004088166,0.00004540675,0.0001268637,0.00003243978,0.0004880997,0.003197655,0.8270199,0.1666222],"study_design_scores_gemma":[0.0001204014,0.0002709041,0.01478149,0.000141808,0.00001071393,0.00008836401,0.0002388752,0.0001846817,0.0003976832,0.001780022,0.9819756,0.000009493224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03353488,0.007810569,0.003746932,0.06231494,0.006891922,0.001277503,0.04357002,0.00292169,0.8379315],"genre_scores_gemma":[0.03876063,0.003354297,0.002208045,0.004408479,0.001281256,0.001052454,0.006058157,0.0002460351,0.9426308],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9993091,"threshold_uncertainty_score":0.8354809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01387732532206729,"score_gpt":0.2375583066764793,"score_spread":0.223680981354412,"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."}}