{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003689367,0.00008310208,0.0001458052,0.00007491708,0.0009792356,0.000109972,0.0002624598,0.00009327351,0.00004912237],"category_scores_gemma":[0.0005318636,0.00006163737,0.0001158403,0.0001475256,0.0003782636,0.0003883489,0.00002780481,0.0004907998,0.000009600132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007219557,"about_ca_system_score_gemma":0.005267036,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001602204,"about_ca_topic_score_gemma":0.04802158,"domain_scores_codex":[0.9975173,0.000298138,0.0002603073,0.0001077781,0.0004078434,0.00140856],"domain_scores_gemma":[0.9992937,0.0001651286,0.0002029328,0.00008133541,0.0001801001,0.00007683326],"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":[0.00003968288,0.00005295198,0.09607157,0.000006662274,0.0001499668,0.00000211265,0.01933832,0.000001310712,0.0004983261,0.7292569,0.0003489216,0.1542333],"study_design_scores_gemma":[0.0005805007,0.0001593383,0.006436496,0.00009130541,0.00005160944,0.00002260345,0.03432228,0.000007259975,0.00005089642,0.932039,0.02602538,0.000213295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316871,0.004248114,0.03981646,0.0136006,0.001708568,0.0001930503,0.000009502261,0.00007478692,0.008661817],"genre_scores_gemma":[0.9914036,0.005153346,0.00005883021,0.00003240417,0.0004802535,9.81756e-7,7.292462e-7,0.00001143592,0.002858415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2027821,"threshold_uncertainty_score":0.9693496,"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."}}