{"id":"W3127004838","doi":"10.5220/0010186703070316","title":"Identifying Geographical Areas using Machine Learning for Enrolling Women in the Canadian Armed Forces","year":2021,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Department of National Defence","funders":"","keywords":"Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001304133,0.0004793018,0.0005592337,0.002774406,0.001961183,0.001492051,0.001950148,0.0007504008,0.002461136],"category_scores_gemma":[0.009178244,0.0002786854,0.0008021214,0.003686611,0.0005142039,0.0006650986,0.001077419,0.001106579,0.0004862927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0120859,"about_ca_system_score_gemma":0.02452177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9884726,"about_ca_topic_score_gemma":0.993836,"domain_scores_codex":[0.9990848,0.0001243967,0.00004229333,0.0001379347,0.0002181355,0.0003923277],"domain_scores_gemma":[0.9978666,0.000540652,0.0002348266,0.0001009296,0.0009272862,0.0003298024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001060019,0.000140978,0.9582167,0.00005618707,0.00009991355,0.00006800899,0.0007211143,0.004468281,0.0002532239,0.0008479116,0.008692541,0.02632924],"study_design_scores_gemma":[0.00002699664,0.00003310144,0.934343,0.0001284084,0.0001202516,0.00003760031,0.007715569,0.05133537,0.0003693463,0.0009868236,0.004866868,0.00003666953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825821,0.0005771444,0.001990191,0.001530856,0.00004568685,0.0001038607,0.009404429,0.00004812538,0.003717715],"genre_scores_gemma":[0.9893756,0.0004209558,0.002444278,0.0001266517,0.00001917114,0.00004944704,0.005844646,0.00001444133,0.001704764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0120859,"threshold_uncertainty_score":0.08768976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0996163094579729,"score_gpt":0.351866430328436,"score_spread":0.2522501208704631,"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."}}