{"id":"W2310868112","doi":"10.5539/mas.v10n3p191","title":"Analysis of Prioritization of the Influencing Factors on Investment and Muscle Drain in Volleyball Clubs in Developing Countries. Case Study: Premier League Club of Iran Volleyball","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Club; Cronbach's alpha; League; Investment (military); Population; Prioritization; Psychology; Validity; Developing country; Descriptive statistics; Business; Medicine; Political science; Environmental health; Economic growth; Statistics; Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0009111575,0.0003504869,0.0002372491,0.002416297,0.001148641,0.001291701,0.0003752676,0.0003986978,0.003127324],"category_scores_gemma":[0.001814373,0.0002136034,0.0003723962,0.00203296,0.0006325739,0.0005586607,0.001119474,0.0003617331,0.0001533539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002341197,"about_ca_system_score_gemma":0.002572623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02217044,"about_ca_topic_score_gemma":0.04970093,"domain_scores_codex":[0.99911,0.0002314926,0.00006577716,0.00008165376,0.000133751,0.0003773297],"domain_scores_gemma":[0.9986344,0.0002808876,0.000460923,0.00002143291,0.0002235786,0.0003787329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008664719,0.00012878,0.9740186,0.0001230658,0.00003815126,0.001597239,0.003836161,0.0002777595,0.0003343586,0.0008668252,0.0007099721,0.01798239],"study_design_scores_gemma":[0.000004333478,0.00008396722,0.9557168,0.00008868012,0.0000249428,0.0004218778,0.04120848,0.0004617114,0.0001620664,0.0001999518,0.001617376,0.000009913661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965094,0.0002478433,0.0001105101,0.0003170021,0.000006401102,0.00002489955,0.00009834465,0.000001766655,0.002683922],"genre_scores_gemma":[0.9991422,0.0001725602,0.0001182532,0.00002316015,0.000003260821,0.000008188952,0.00005268398,8.213005e-7,0.0004788717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02217044,"threshold_uncertainty_score":0.04408276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03726549651442428,"score_gpt":0.3044384526439703,"score_spread":0.2671729561295461,"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."}}