{"id":"W4254289862","doi":"10.4095/301112","title":"Growth Rate of Leisure Services Employment, 1986 to 1996","year":2010,"lang":"en","type":"report","venue":"","topic":"Recreation, Leisure, Wilderness Management","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Labour economics; Demographic economics; Economics","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":[0.0007834126,0.0006440541,0.0002977537,0.003942137,0.0005018638,0.001024731,0.0009918985,0.0004621183,0.004998147],"category_scores_gemma":[0.003373685,0.0003141994,0.0003804225,0.005749589,0.0001892304,0.0008343259,0.00104364,0.0008586228,0.006037664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002668399,"about_ca_system_score_gemma":0.001821787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2144158,"about_ca_topic_score_gemma":0.2299083,"domain_scores_codex":[0.9992384,0.00005656064,0.0001392267,0.0001352875,0.00027227,0.0001582018],"domain_scores_gemma":[0.9968267,0.0002072661,0.001085734,0.0001050822,0.001401932,0.0003732204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005615994,0.0001628786,0.888688,0.0004110478,0.00010241,0.0003329719,0.0006174272,0.0008180963,0.000511426,0.0004043659,0.05570808,0.05168171],"study_design_scores_gemma":[0.00001450495,0.00003612705,0.9674852,0.00006980287,0.00001516946,0.0001970534,0.0002235019,0.0001779696,0.0002764514,0.00001451257,0.03148301,0.000006656715],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4341819,0.003673598,0.0006280782,0.001171147,0.0002380372,0.0002045191,0.5316215,0.0002947837,0.02798652],"genre_scores_gemma":[0.4568895,0.007835321,0.001055486,0.0004198301,0.0002073596,0.000350046,0.4551463,0.0000963442,0.07799975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2144158,"threshold_uncertainty_score":0.4263356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03699886384032578,"score_gpt":0.3542529123877974,"score_spread":0.3172540485474716,"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."}}