{"id":"W7115823662","doi":"","title":"Inversiones financieras y resultados deportivos en las grandes ligas de fútbol: un análisis comparativo entre el valor de mercado, el salario base y los resultados en las conferencias","year":2025,"lang":"es","type":"article","venue":"Dialnet (Universidad de la Rioja)","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Salary; League; Miami; Financial compensation; Compensation (psychology); Base (topology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006190529,0.0005450558,0.0005904194,0.001924752,0.0005445539,0.002261894,0.0005525626,0.0004717957,0.00546093],"category_scores_gemma":[0.01531176,0.0002345957,0.001002147,0.001743102,0.0005208845,0.0010492,0.00176646,0.0008345287,0.0009637801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352217,"about_ca_system_score_gemma":0.001093919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0180022,"about_ca_topic_score_gemma":0.02108235,"domain_scores_codex":[0.9977877,0.000751592,0.0001741911,0.0002469246,0.0005450596,0.0004945749],"domain_scores_gemma":[0.9877105,0.005378257,0.00382494,0.0004237143,0.001657174,0.001005421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001992385,0.0003557496,0.946862,0.0001492985,0.0003493958,0.0001655017,0.001309914,0.001216647,0.0004089033,0.0004815757,0.0008189886,0.04588975],"study_design_scores_gemma":[0.000050252,0.0005871466,0.9905749,0.0001346402,0.0002991821,0.0001134211,0.002916146,0.001123057,0.0007453976,0.0003896255,0.003042503,0.00002384136],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921458,0.0009960636,0.0008599183,0.0002484824,0.00002571182,0.00002600835,0.0008002706,0.0000389773,0.004858719],"genre_scores_gemma":[0.9959531,0.0004897313,0.0004943571,0.00003752159,0.00003942048,0.00004344064,0.0007225314,0.00001609293,0.002203895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0180022,"threshold_uncertainty_score":0.03579479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193957107497868,"score_gpt":0.2483835792187825,"score_spread":0.2364440081438039,"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."}}