{"id":"W4401789389","doi":"10.1177/2694105820220202003","title":"Conflict Analytics: When Data Science Meets Dispute Resolution","year":2022,"lang":"en","type":"article","venue":"Management and business review.","topic":"Qualitative Comparative Analysis Research","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; McGill University","funders":"","keywords":"Analytics; Data science; Dispute resolution; Data analysis; Conflict resolution; Online dispute resolution; Computer science; Political science; Alternative dispute resolution; Data mining; Law","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":[0.1561235,0.001193726,0.002633844,0.0143913,0.007521423,0.03897716,0.004186651,0.009769644,0.01333368],"category_scores_gemma":[0.400528,0.001699155,0.001622049,0.01758883,0.02382731,0.0869358,0.01981947,0.01232124,0.003195102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008077763,"about_ca_system_score_gemma":0.01288456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003858001,"about_ca_topic_score_gemma":0.003031633,"domain_scores_codex":[0.8272445,0.121823,0.01218745,0.00870816,0.02586404,0.004172726],"domain_scores_gemma":[0.5175005,0.4219438,0.01215817,0.02230036,0.02126337,0.004833797],"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":[0.0002524822,0.00007010187,0.005497132,0.001369247,0.0001099357,0.0003220652,0.007279227,0.001122316,0.0001853554,0.8489709,0.03850731,0.09631391],"study_design_scores_gemma":[0.00003711321,0.00002967791,0.000550881,0.001396982,0.00002658875,0.0001332014,0.005213439,0.003275108,0.0002636007,0.9304848,0.0585489,0.00003966332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02427042,0.05289951,0.2743868,0.4729773,0.006986062,0.001052401,0.001836588,0.001065594,0.1645253],"genre_scores_gemma":[0.6848843,0.02100614,0.2354193,0.03820063,0.006589916,0.002577171,0.002418213,0.001039906,0.007864316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1561235,"threshold_uncertainty_score":0.8256697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2645313786086008,"score_gpt":0.4775478889267745,"score_spread":0.2130165103181736,"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."}}