{"id":"W3121200831","doi":"","title":"Sticks and Stones: Language, Face, and Online Dispute Resolution","year":2012,"lang":"en","type":"article","venue":"Hispana","topic":"Conflict Management and Negotiation","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Settlement (finance); Face (sociological concept); Resolution (logic); Event (particle physics); Affect (linguistics); Social psychology; Dispute resolution; Psychology; Political science; Law and economics; Business; Economics; Computer science; Law; Linguistics; Artificial intelligence; Communication; Philosophy; Finance","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":[0.006114117,0.0002416617,0.0003442693,0.001440917,0.001796898,0.005147143,0.0007789836,0.001257494,0.01062554],"category_scores_gemma":[0.05684595,0.0002577859,0.0003811213,0.0009704715,0.003165123,0.006834699,0.00269452,0.001564693,0.0007135774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007534063,"about_ca_system_score_gemma":0.0004367472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001207103,"about_ca_topic_score_gemma":0.00076595,"domain_scores_codex":[0.9932613,0.004738279,0.0002412613,0.0003506851,0.001009474,0.000398894],"domain_scores_gemma":[0.9514029,0.03770148,0.006904132,0.001675379,0.001135765,0.001180389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.002670268,0.001768803,0.3996217,0.0004897731,0.0003440126,0.002456737,0.219652,0.004542199,0.005598959,0.1107386,0.004099823,0.2480172],"study_design_scores_gemma":[0.0002883161,0.00108103,0.5003589,0.0005990805,0.0002411926,0.003207725,0.183979,0.04526684,0.003548678,0.2431751,0.01787507,0.0003790362],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558431,0.0002761045,0.004976092,0.001119038,0.00002746613,0.00005116142,0.00005255569,0.00001863388,0.03763588],"genre_scores_gemma":[0.9978129,0.00004841724,0.0008587728,0.0001024256,0.00002239992,0.00001831797,0.00002037438,0.000007000027,0.001109399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01062554,"threshold_uncertainty_score":0.035546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02470704013157689,"score_gpt":0.3211247428608703,"score_spread":0.2964177027292934,"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."}}