{"id":"W38980156","doi":"10.1021/acsami.4c07282","title":"Содержание и соотношение понятий «Правовая фикция» и «Фиктивная норма»","year":2012,"lang":"en","type":"article","venue":"Социально-политические науки","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Materials Research; Narodowe Centrum Nauki; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Legislator; Phenomenon; Norm (philosophy); Law; Legislature; Epistemology; Legal norm; Enforcement; Political science; Law and economics; Legislation; Sociology; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002487038,0.0005382646,0.0007083418,0.0004643394,0.001892004,0.0002862963,0.001065266,0.0005402219,0.006264672],"category_scores_gemma":[0.0003013711,0.0004726469,0.0006222701,0.00194093,0.0009566835,0.001620239,0.000245622,0.0006253623,0.00370444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003612725,"about_ca_system_score_gemma":0.0003530653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001814974,"about_ca_topic_score_gemma":0.001773365,"domain_scores_codex":[0.9943973,0.0007385183,0.0007214194,0.000687206,0.001452459,0.002003082],"domain_scores_gemma":[0.9970638,0.0002748991,0.0003200212,0.00091454,0.0002469574,0.001179846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002220689,0.002555633,0.1641686,0.0002105754,0.001317933,0.0001086918,0.08672782,0.0001581605,0.004543683,0.5067264,0.1404132,0.09284717],"study_design_scores_gemma":[0.0006452074,0.00005984548,0.02412775,0.00004762353,0.0002631055,0.0000110464,0.00411119,0.00005419894,0.001153463,0.003433715,0.9651531,0.0009397264],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4582093,0.004048587,0.0005525742,0.007395951,0.004412218,0.0007816001,0.00004836088,0.001058451,0.5234929],"genre_scores_gemma":[0.9362218,0.0001666906,0.0004858783,0.001362215,0.003952351,0.00005826879,0.00003403845,0.00007345728,0.05764531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8247399,"threshold_uncertainty_score":0.9997725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02219138236811459,"score_gpt":0.3245973875977288,"score_spread":0.3024060052296142,"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."}}