{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005553891,0.0001256213,0.0003278243,0.00008723764,0.00008176325,0.000005395011,0.0001848227,0.0001505109,0.0007509945],"category_scores_gemma":[0.0001396896,0.0001162264,0.00004257398,0.0001222129,0.0002388511,0.000037493,0.00004895968,0.0001260421,8.300193e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003466379,"about_ca_system_score_gemma":0.01057204,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9997103,"about_ca_topic_score_gemma":0.9999298,"domain_scores_codex":[0.9984593,0.00008775333,0.0002849026,0.0002326663,0.000685799,0.0002495265],"domain_scores_gemma":[0.9994279,0.00007290689,0.00006609116,0.0001606126,0.0001817283,0.00009081364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000414279,0.0001154389,0.2896624,0.001318319,0.0002470004,0.0001575585,0.1885776,7.901418e-7,0.00003229607,0.001084183,0.4869514,0.0318116],"study_design_scores_gemma":[0.0001198403,0.00003700479,0.0412717,0.00007933256,0.00002047817,0.000002816942,0.05297467,0.000003664466,0.00001350641,0.0003412206,0.9048985,0.0002372097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3286494,0.006969534,4.306985e-7,0.0001623761,0.0008372235,0.0001794738,0.00003686857,0.000006827091,0.6631578],"genre_scores_gemma":[0.9788784,0.01535415,0.00003384255,0.0001070665,0.0002795181,0.000007312887,0.00002574694,0.000007985751,0.00530599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6578519,"threshold_uncertainty_score":0.9950371,"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."}}