{"id":"W7029025060","doi":"","title":"The ICT gender imbalance in schools and beyond : missed opportunities","year":2010,"lang":"en","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"History and Cultural Heritage","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Normative; Attrition; Information and Communications Technology; Government (linguistics); Quarter (Canadian coin); Theory of planned behavior; Focus group","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":[0.004076769,0.0003460036,0.0006763915,0.001226164,0.006731439,0.004711077,0.0008795291,0.001282573,0.005227691],"category_scores_gemma":[0.006021874,0.0004519917,0.0003848288,0.001033327,0.004218678,0.006296426,0.006396379,0.001905235,0.0004041893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003267147,"about_ca_system_score_gemma":0.004594852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008351346,"about_ca_topic_score_gemma":0.02891547,"domain_scores_codex":[0.996877,0.001077468,0.0001074915,0.0002698757,0.0005771117,0.001091131],"domain_scores_gemma":[0.9959269,0.001297961,0.0009958921,0.0001901689,0.0003301129,0.001258894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001838387,0.0001512946,0.1442189,0.0003536228,0.00001672845,0.002234209,0.6527737,0.00007872292,0.001056291,0.01821886,0.00717335,0.1735405],"study_design_scores_gemma":[0.000006628818,0.0001694415,0.08926634,0.0004218548,0.0000161985,0.0008227699,0.8672834,0.00008225725,0.0003267161,0.004986891,0.03658376,0.00003373694],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760442,0.002470483,0.0004219211,0.01057111,0.0002296329,0.00001531662,0.00005735044,0.00001810654,0.01017186],"genre_scores_gemma":[0.9972005,0.0004587699,0.0001006758,0.0004889932,0.00002990568,0.000009973786,0.00001346247,0.000005587802,0.001692081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008351346,"threshold_uncertainty_score":0.02370495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04297458640040089,"score_gpt":0.2951557346623186,"score_spread":0.2521811482619177,"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."}}