{"id":"W4403975913","doi":"10.61959/cyth4819e","title":"A Snapshot of Military and Veteran Families in Canada","year":2018,"lang":"en","type":"report","venue":"","topic":"Gender, Security, and Conflict","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snapshot (computer storage); Genealogy; Geography; History; Computer science; Database","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":[0.001106578,0.0006060347,0.0006407217,0.005046853,0.01720549,0.00445277,0.002119956,0.001008347,0.01040242],"category_scores_gemma":[0.002667896,0.0005817703,0.0006189246,0.01221433,0.001334142,0.002246245,0.004154375,0.002623908,0.0009843465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09360652,"about_ca_system_score_gemma":0.2131675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9972656,"about_ca_topic_score_gemma":0.9990043,"domain_scores_codex":[0.9976661,0.0001513191,0.0001170527,0.0001266684,0.0006788928,0.001260031],"domain_scores_gemma":[0.9937938,0.0002307605,0.0002320544,0.00007770365,0.003029062,0.002636622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002206098,0.000224966,0.2148239,0.001449604,0.000120511,0.004657416,0.1528815,0.0003581691,0.0007831612,0.005122356,0.4944847,0.1248732],"study_design_scores_gemma":[0.000024242,0.0000731654,0.3287543,0.002655345,0.00006849481,0.001808172,0.2909609,0.0001714067,0.0002767721,0.000635479,0.3744037,0.0001680368],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.64577,0.04886735,0.001034876,0.05100637,0.001564464,0.001230566,0.1256712,0.0003037861,0.1245514],"genre_scores_gemma":[0.8235553,0.06647016,0.003579775,0.0185299,0.0003708867,0.001075509,0.03136096,0.0002257623,0.05483176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09360652,"threshold_uncertainty_score":0.6791661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210241748868986,"score_gpt":0.3099206326137663,"score_spread":0.2578182151250764,"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."}}