{"id":"W2792669608","doi":"","title":"SETTLEMENT COUNSEL: AN INNOVATIVE STRATEGY FOR THE MANAGEMENT AND RESOLUTION OF COMMERCIAL LITIGATION FILES","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Settlement (finance); Negotiation; Accountability; Incentive; Construct (python library); Work (physics); Dispute resolution; Political science; Law; Business; Law and economics; Public relations; Engineering; Economics; Finance; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02027559,0.0004834544,0.0004310431,0.004285509,0.01322661,0.0125334,0.004378433,0.003926046,0.0253977],"category_scores_gemma":[0.03783323,0.0005343245,0.0005018114,0.00276113,0.00572022,0.009577611,0.01576185,0.003367968,0.005129269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004217925,"about_ca_system_score_gemma":0.03559635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007619183,"about_ca_topic_score_gemma":0.02181784,"domain_scores_codex":[0.9835385,0.008870266,0.0004602523,0.00125874,0.004425874,0.001446399],"domain_scores_gemma":[0.9884846,0.005402269,0.001052689,0.001550217,0.001166274,0.002344066],"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":[0.0001289254,0.0004498069,0.00462754,0.0001484885,0.0000249713,0.001250168,0.06008095,0.001363826,0.003049046,0.438136,0.07270005,0.4180402],"study_design_scores_gemma":[0.0001590493,0.0002931772,0.003687336,0.0003511739,0.00003776622,0.001925057,0.062814,0.008365233,0.002774522,0.1333011,0.786109,0.0001825615],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1228358,0.0007525619,0.439766,0.03362955,0.0008839432,0.003203234,0.0003990275,0.003511461,0.3950183],"genre_scores_gemma":[0.5929486,0.0005249333,0.2675316,0.003502596,0.0002892583,0.001790598,0.0002101106,0.0003952758,0.132807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0253977,"threshold_uncertainty_score":0.1072289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06023909209695339,"score_gpt":0.4041586855270993,"score_spread":0.3439195934301459,"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."}}