{"id":"W2952093094","doi":"10.1108/sbm-04-2018-0028","title":"Catch and release? NHL expansion draft endowment effects","year":2019,"lang":"en","type":"article","venue":"Sport Business and Management An International Journal","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Context (archaeology); Affect (linguistics); Endowment; Athletes; Premise; Selection bias; Originality; Psychology; Natural experiment; Actuarial science; Cognitive bias; Marketing; Business; Economics; Social psychology; Cognition; Political 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":[0.0002813183,0.0001267044,0.0002043216,0.0002717582,0.00008903768,0.0002605908,0.0001724651,0.00003612392,0.0003813345],"category_scores_gemma":[0.00000303091,0.0001225774,0.0000379959,0.00008768413,0.00002450032,0.0005601134,0.00009792217,0.00009553026,0.00005561009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004297609,"about_ca_system_score_gemma":0.000007599833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002003498,"about_ca_topic_score_gemma":0.00001370509,"domain_scores_codex":[0.9991165,0.000001905016,0.0003484501,0.0002667357,0.0001037266,0.0001627147],"domain_scores_gemma":[0.9994403,0.000004199041,0.0002448241,0.0001385988,0.00008009191,0.00009200714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006267762,0.0001168489,0.7881945,0.00009744572,0.0001749078,0.0001545282,0.0001616994,0.0002537552,0.00001138101,0.1953614,0.0004973485,0.01491356],"study_design_scores_gemma":[0.0009325522,0.00004584901,0.8772771,0.00007656387,0.00001397659,0.00006224267,0.00006466912,0.002817717,0.000008230842,0.003890193,0.1146172,0.0001936957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871121,0.0006258824,0.0008806885,0.0006740729,0.001489606,0.0001686742,0.000007006161,0.00001227633,0.009029681],"genre_scores_gemma":[0.9863988,0.009793445,0.000296215,0.0004248696,0.0002537023,0.000006275588,0.00002882006,0.00001414404,0.002783723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1914712,"threshold_uncertainty_score":0.4998563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009130274910376717,"score_gpt":0.2105507602311812,"score_spread":0.2014204853208045,"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."}}