{"id":"W2620376036","doi":"10.22552/jijmr/2017/v3/i1/146082","title":"Improving Olympic Performance of India via Principles of Management","year":2017,"lang":"en","type":"article","venue":"Jaipuria International Journal of Management Research","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Incentive; Theme (computing); Athletes; State (computer science); Business; Process (computing); State policy; Sport management; Public relations; Marketing; Political science; Public administration; Economics; Computer science; Market economy; Policy analysis","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":[0.001363905,0.0005125272,0.000200565,0.001267313,0.002320889,0.005583962,0.001129765,0.0007482999,0.003317903],"category_scores_gemma":[0.001181935,0.0001517178,0.0003067626,0.001056274,0.003747592,0.000990606,0.002908684,0.001556968,0.0006200777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004374421,"about_ca_system_score_gemma":0.009151155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00911365,"about_ca_topic_score_gemma":0.02093413,"domain_scores_codex":[0.9986603,0.0003439375,0.00006692376,0.000122064,0.0005550284,0.0002517918],"domain_scores_gemma":[0.9993686,0.00008561121,0.000122076,0.00005154733,0.0002246245,0.0001476148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002814557,0.0002315952,0.006987046,0.0004566719,0.00003350791,0.0002245804,0.007237982,0.003478857,0.00149815,0.7855576,0.02827767,0.1659882],"study_design_scores_gemma":[0.00003260216,0.0004089084,0.04289524,0.0007277564,0.00006417937,0.0004450808,0.01184592,0.003533744,0.00181293,0.1696736,0.7684666,0.000093529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0379601,0.003543323,0.04045688,0.03510685,0.0006922858,0.0003988536,0.0001476449,0.0003489176,0.8813452],"genre_scores_gemma":[0.8263021,0.004934321,0.05086952,0.003081257,0.0003991532,0.0004875137,0.0001094247,0.00009887625,0.1137179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00911365,"threshold_uncertainty_score":0.03173876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09796217279968632,"score_gpt":0.4244353395712177,"score_spread":0.3264731667715314,"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."}}