{"id":"W2917139413","doi":"10.1111/ncmr.12154","title":"When the <scp>SUIT</scp> Fits: Constructive Controversy Training in Face‐to‐Face and Virtual Teams","year":2019,"lang":"en","type":"article","venue":"Negotiation and Conflict Management Research","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Alberta; University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Constructive; Scope (computer science); Task (project management); Computer science; Face (sociological concept); Teamwork; Knowledge management; Work (physics); Face-to-face; Psychology; Process (computing); Management; Engineering; Sociology; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001204007,0.0001357493,0.0001790054,0.0003008062,0.0001631724,0.0001658404,0.0002323544,0.0000851556,0.0002077302],"category_scores_gemma":[0.00006077015,0.000110561,0.00002231489,0.0002954161,0.000149012,0.0001377403,0.0001997816,0.0003989364,0.0002105093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005419047,"about_ca_system_score_gemma":0.00002583121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002263593,"about_ca_topic_score_gemma":0.000104224,"domain_scores_codex":[0.998302,0.0002225427,0.0002147494,0.0004088916,0.0003783151,0.0004734764],"domain_scores_gemma":[0.9989577,0.0005314033,0.00005623253,0.0002931118,0.00006389483,0.00009764702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001321376,0.00007793966,0.08384531,0.00007416349,0.0002436242,0.00001612942,0.184944,0.0002222139,0.0002590655,0.51228,0.006034039,0.2118713],"study_design_scores_gemma":[0.00389356,0.0005270293,0.4155695,0.00006943056,0.00001701119,0.000009576524,0.2612765,0.0106465,0.00001448957,0.0008618372,0.306979,0.0001355952],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906127,0.0001763874,0.0004450748,0.001315428,0.0002246878,0.001280702,0.00001500259,0.0000244958,0.09039121],"genre_scores_gemma":[0.9769271,0.0001514897,0.00004211433,0.0006852889,0.00004250023,0.00009832779,0.00001035812,0.00001395469,0.02202884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5114182,"threshold_uncertainty_score":0.4508545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03686262402860451,"score_gpt":0.347523045749667,"score_spread":0.3106604217210625,"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."}}