{"id":"W2107365024","doi":"10.1111/j.1571-9979.2003.tb00782.x","title":"Bringing Horses to Water? Overcoming Bad Relationships in the Pre-Negotiating Stage of Consensus Building","year":2003,"lang":"en","type":"article","venue":"Negotiation Journal","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Appeal; Negotiation; Incentive; Public relations; Political science; Process (computing); Business; Economics; Law; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01740336,0.0001159989,0.0001996175,0.0005483035,0.000519753,0.0004639999,0.0003704167,0.0000536325,0.0006169632],"category_scores_gemma":[0.007584512,0.00007100654,0.00007699095,0.0007389123,0.00002735764,0.0004727708,0.00003475243,0.0004536679,0.00003700995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001132687,"about_ca_system_score_gemma":0.0001883554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002365525,"about_ca_topic_score_gemma":0.00005102817,"domain_scores_codex":[0.9952337,0.001453025,0.00117728,0.0002085002,0.001637844,0.0002896474],"domain_scores_gemma":[0.9965879,0.002135597,0.0004906558,0.0002790033,0.0004158537,0.00009100771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003252537,0.0000557955,0.4481874,0.000008197625,0.0000159459,0.000006829897,0.02543442,0.4940048,0.009132286,0.01583134,0.0007504261,0.006540097],"study_design_scores_gemma":[0.002100951,0.0002285607,0.7673,0.0002200814,0.00003411542,0.0002641907,0.04006829,0.1238506,0.01482682,0.01145168,0.03916482,0.0004898432],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9641128,0.00004378397,0.02965633,0.00169475,0.0005265485,0.0002197963,0.00000255339,0.00000876629,0.003734628],"genre_scores_gemma":[0.9926389,0.00000674181,0.006555907,0.0002125104,0.000104019,0.000005672086,8.757246e-7,0.000008164368,0.0004672511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701541,"threshold_uncertainty_score":0.9079916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1881038449592963,"score_gpt":0.4518151814544571,"score_spread":0.2637113364951609,"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."}}