{"id":"W2939566549","doi":"10.1037/apl0000407","title":"Efficient proximal resource allocation strategies predict distal team performance: Evidence from the National Hockey League.","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Psychology","topic":"Behavioral Health and Interventions","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"PsycINFO; League; Resource allocation; Variance (accounting); Psychology; Resource (disambiguation); Operations management; Business; Computer science; Economics; MEDLINE; Management; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001091852,0.0001645108,0.0002571752,0.0001191071,0.0001367054,0.00004391597,0.0005287403,0.0001927775,0.001571407],"category_scores_gemma":[0.00002200925,0.0001144352,0.0001472619,0.0002004236,0.0001641624,0.0001091231,0.00003721595,0.0007518362,0.0004926538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008907306,"about_ca_system_score_gemma":0.0001594314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002389559,"about_ca_topic_score_gemma":0.000009020198,"domain_scores_codex":[0.9979497,0.0001496681,0.000800708,0.0002894675,0.0004816631,0.000328848],"domain_scores_gemma":[0.9985093,0.0002237379,0.0006392657,0.0002957313,0.0002204813,0.0001114154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.02121462,0.005259748,0.1358277,0.0001391577,0.0007087143,0.00002410042,0.0221829,0.008879356,0.02276392,0.02785722,0.6457103,0.1094322],"study_design_scores_gemma":[0.002828541,0.001994606,0.944236,0.0002159239,0.00008526191,0.0001516992,0.004234157,0.000600043,0.000117189,0.00079712,0.04449301,0.0002464412],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637301,0.0004313753,0.0003600745,0.001409776,0.001247371,0.0004257598,0.00002207204,0.00002150345,0.03235196],"genre_scores_gemma":[0.9976642,0.00002606224,0.000214142,0.0009662295,0.0006943651,0.0000417905,0.00001730791,0.00001832614,0.0003575847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8084083,"threshold_uncertainty_score":0.9993413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05634077088221322,"score_gpt":0.3877049255657265,"score_spread":0.3313641546835133,"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."}}