{"id":"W2579677293","doi":"","title":"Политические факторы развития канадской армии во время Второй мировой войны","year":2016,"lang":"ru","type":"article","venue":"Власть","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dominion; Politics; Political science; State (computer science); Law; Mathematics","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009761496,0.0004181046,0.0005891475,0.0007424005,0.002327051,0.0008671001,0.001145904,0.0005915113,0.0297895],"category_scores_gemma":[0.000516133,0.0004332723,0.0004682503,0.0008548374,0.002312605,0.0008153773,0.0001910212,0.0004197549,0.02527746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002628229,"about_ca_system_score_gemma":0.002621175,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2861517,"about_ca_topic_score_gemma":0.773214,"domain_scores_codex":[0.9954993,0.0003736848,0.0006583121,0.0009320424,0.00109575,0.00144093],"domain_scores_gemma":[0.9972171,0.000315129,0.0003322472,0.0008720129,0.0002240983,0.001039375],"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":[0.00005687742,0.0002518148,0.001645033,0.0001000387,0.0001549187,0.0002009776,0.01815271,0.000001384597,0.001308662,0.0606255,0.737376,0.1801261],"study_design_scores_gemma":[0.0008110946,0.00009843945,0.00369642,0.0002212257,0.0001076008,0.000007310805,0.001605066,0.000004031035,0.00007436863,0.002914753,0.9897445,0.0007151438],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06695892,0.009111954,0.0002535285,0.04311708,0.01540841,0.001093293,0.0008143628,0.0005535565,0.8626889],"genre_scores_gemma":[0.3721282,0.003528273,0.0001239891,0.00168786,0.003700726,0.00003990251,0.00001233371,0.00009700591,0.6186817],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4870623,"threshold_uncertainty_score":0.9998119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0107073312087701,"score_gpt":0.2158983240276668,"score_spread":0.2051909928188967,"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."}}