{"id":"W6906460957","doi":"10.17605/osf.io/yxwaz","title":"Daily Experiences of Diverse Canadian Armed Forces Women Working in the Royal Canadian Navy","year":2024,"lang":"en","type":"other","venue":"Open Science Framework","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sample (material); Navy; Government (linguistics); Work (physics)","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":[0.003375353,0.0004803039,0.0006158336,0.002523445,0.02492744,0.005119125,0.002019739,0.001172278,0.01653101],"category_scores_gemma":[0.007700196,0.0004089553,0.0004190629,0.003705001,0.004312009,0.001137058,0.004923989,0.001607776,0.002294998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03473704,"about_ca_system_score_gemma":0.06261676,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9799055,"about_ca_topic_score_gemma":0.9921062,"domain_scores_codex":[0.9961886,0.0006338682,0.00009563965,0.0001574041,0.001078988,0.001845586],"domain_scores_gemma":[0.9937412,0.0008959018,0.0003588494,0.0001464075,0.002167734,0.002689857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002337836,0.00007081428,0.03146578,0.0003312621,0.00001940484,0.001025228,0.8099643,0.0001082386,0.001013561,0.003293463,0.1029161,0.04955811],"study_design_scores_gemma":[0.000006529197,0.0000364649,0.034254,0.0002268185,0.000008213962,0.0001404721,0.8537624,0.00003211186,0.0001375116,0.0001613155,0.1111609,0.00007321094],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7898397,0.003849411,0.0009461904,0.02116196,0.0008954477,0.0006042405,0.007338341,0.0001866337,0.1751781],"genre_scores_gemma":[0.8694071,0.004744592,0.001444549,0.005942417,0.000161551,0.0004941936,0.001512804,0.0001881958,0.1161046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03473704,"threshold_uncertainty_score":0.252036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02987587680927261,"score_gpt":0.3111452172845445,"score_spread":0.2812693404752719,"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."}}