{"id":"W3117517364","doi":"10.2139/ssrn.2798011","title":"Behind Union Lines: Setting of Evidentiary Boundaries","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Social Power and Status Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; University of Toronto","funders":"","keywords":"Negotiation; Subject (documents); Feature (linguistics); Sociology; State (computer science); Order (exchange); Phenomenon; Epistemology; Law and economics; Political science; Law; Computer science; Linguistics; Business; Philosophy; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008428222,0.0002315665,0.0005332482,0.002555792,0.0107807,0.01392042,0.002299778,0.004759098,0.02020975],"category_scores_gemma":[0.04746687,0.0006133067,0.0004865162,0.001623976,0.01573871,0.0135156,0.009685027,0.004620827,0.001372367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003362198,"about_ca_system_score_gemma":0.004527972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003600603,"about_ca_topic_score_gemma":0.005073539,"domain_scores_codex":[0.9918646,0.003495436,0.0005079457,0.001260646,0.001471829,0.00139959],"domain_scores_gemma":[0.9826349,0.00909818,0.002299492,0.002300417,0.002382564,0.001284386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006078407,0.00003666076,0.002329403,0.00002794509,0.00000482031,0.0001611825,0.02330597,0.0003431938,0.0004342288,0.9614583,0.0007840127,0.01105355],"study_design_scores_gemma":[0.00006151813,0.0001450777,0.01340583,0.0003715795,0.00002589804,0.0002119981,0.07101614,0.003241125,0.001200327,0.8733798,0.03688031,0.00006044396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4334201,0.0004048338,0.07004353,0.006488404,0.0002084569,0.0001976343,0.0001332191,0.0001231097,0.4889806],"genre_scores_gemma":[0.9918481,0.00003582061,0.002923377,0.00007834252,0.00001608999,0.00003409143,0.00002126272,0.00002029661,0.005022612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02020975,"threshold_uncertainty_score":0.06760836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007588005032348316,"score_gpt":0.2924235678589423,"score_spread":0.284835562826594,"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."}}