{"id":"W2132130844","doi":"10.1007/s10726-006-9024-z","title":"Comparative Analysis of Text Data in Successful Face-to-Face and Electronic Negotiations","year":2006,"lang":"en","type":"article","venue":"Group Decision and Negotiation","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Negotiation; Vocabulary; Face (sociological concept); Generalization; Artificial intelligence; Natural language processing; Similarity (geometry); Face-to-face; Linguistics; Sociology; Epistemology; Social science","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":[0.007270026,0.0003324759,0.0005614148,0.004834551,0.001105254,0.003024046,0.0009605143,0.001263887,0.005615104],"category_scores_gemma":[0.1011623,0.0002128048,0.0004006002,0.005524377,0.001077156,0.003652769,0.001071648,0.001064382,0.002054024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007565021,"about_ca_system_score_gemma":0.000616395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001347978,"about_ca_topic_score_gemma":0.001610548,"domain_scores_codex":[0.9914379,0.005043762,0.0007569334,0.0005587554,0.001904006,0.0002987434],"domain_scores_gemma":[0.6967139,0.2815628,0.006175333,0.003669677,0.01113931,0.000738925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0216214,0.003282209,0.1943932,0.005588579,0.0007167531,0.005399357,0.03930718,0.02410062,0.06085574,0.02785667,0.01997768,0.5969006],"study_design_scores_gemma":[0.0005287653,0.001994454,0.5124953,0.0009013579,0.000901125,0.003372871,0.04528584,0.2763295,0.06687828,0.04842119,0.04234282,0.0005484025],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688666,0.0007635424,0.01614717,0.0006789765,0.000119223,0.0002308153,0.003739123,0.0003549625,0.009099632],"genre_scores_gemma":[0.9826304,0.0002527263,0.009039586,0.0000693206,0.0000735876,0.0002445516,0.005233947,0.0001353682,0.002320444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007270026,"threshold_uncertainty_score":0.03844804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173132733298819,"score_gpt":0.3130393345252505,"score_spread":0.2957260611953685,"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."}}