{"id":"W2067098066","doi":"10.1111/j.0002-9092.2004.00612.x","title":"The Fast Decay Process in Outdoor Recreational Activities and the Use of Alternative Count Data Models","year":2004,"lang":"en","type":"article","venue":"American Journal of Agricultural Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Count data; Recreation; Popularity; Econometrics; Process (computing); Econometric model; Variable (mathematics); Statistics; Computer science; Economics; Mathematics; Ecology; Psychology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006103684,0.0001093777,0.0003721885,0.00005222332,0.00008622655,0.00008576216,0.0003548367,0.00002261463,0.0000059292],"category_scores_gemma":[0.00004276304,0.00006423234,0.0000615332,0.00006389055,0.0004931134,0.001259485,0.00007726227,0.0001380257,0.000003056289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002180543,"about_ca_system_score_gemma":0.00003569296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004544366,"about_ca_topic_score_gemma":0.0001947364,"domain_scores_codex":[0.998911,0.00002636946,0.0007408048,0.0001650787,0.00002994782,0.0001268123],"domain_scores_gemma":[0.9980993,0.000255835,0.001411557,0.0001692892,0.00002427743,0.00003968905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003582424,0.0001101694,0.03955148,0.000008575289,0.0003362994,7.370253e-7,0.0056141,0.7644351,0.000009671214,0.1822892,0.00008145246,0.007204992],"study_design_scores_gemma":[0.008225888,0.0006484243,0.8097382,0.000139573,0.00008426966,0.0002035414,0.03140422,0.04228687,0.0003832164,0.104329,0.001803151,0.0007536981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967322,0.0003913566,0.000467841,0.00179866,0.0001069751,0.0001319093,0.0001222304,0.000001352283,0.0002474122],"genre_scores_gemma":[0.9947595,0.004396375,0.00061312,0.0001025471,0.00006980667,0.000005413817,0.00001408244,0.000006835143,0.00003233218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7701867,"threshold_uncertainty_score":0.2619318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1082856701103029,"score_gpt":0.2305299223718851,"score_spread":0.1222442522615822,"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."}}