{"id":"W4322487729","doi":"10.1016/j.jort.2023.100615","title":"Understanding the role of traditional and user-created recreation data in the cumulative footprint of recreation","year":2023,"lang":"en","type":"article","venue":"Journal of Outdoor Recreation and Tourism","topic":"Recreation, Leisure, Wilderness Management","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nature Conservancy of Canada; Government of British Columbia; University of Northern British Columbia","funders":"","keywords":"Recreation; Government (linguistics); Wildlife; Geography; Environmental resource management; Footprint; Environmental planning; Ecology; Environmental science; Archaeology","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":[0.002602466,0.0001559852,0.0003349626,0.0004593992,0.0001219686,0.00005451198,0.0003192658,0.0001101309,0.00007627285],"category_scores_gemma":[0.0002651725,0.0001027149,0.00006579626,0.0005989969,0.0001555754,0.0003075814,0.00004984927,0.0002278587,0.000002166202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008256573,"about_ca_system_score_gemma":0.00005254594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003470069,"about_ca_topic_score_gemma":0.00005226403,"domain_scores_codex":[0.9976779,0.0005903,0.0008376955,0.0002309317,0.0005056529,0.0001574962],"domain_scores_gemma":[0.9973871,0.00100692,0.0009813803,0.0003945708,0.0001775776,0.00005246526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00198481,0.001027834,0.522705,0.0001824805,0.001321751,0.00006302309,0.0449025,0.001382632,0.002597918,0.3352092,0.007370085,0.08125277],"study_design_scores_gemma":[0.00190208,0.0003798195,0.9302793,0.0002886264,0.0002456342,0.00006922531,0.02473504,0.003140893,0.0003432663,0.03446908,0.003996782,0.000150242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774256,0.0006781936,0.00658591,0.002600899,0.0002644869,0.0009459087,0.00004206996,0.00002084417,0.01143613],"genre_scores_gemma":[0.9978317,0.0009293176,0.0005165692,0.00001466801,0.0001592402,0.0000238411,0.0001245592,0.00001677932,0.000383323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4075743,"threshold_uncertainty_score":0.4188592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2107070938377826,"score_gpt":0.356361491095336,"score_spread":0.1456543972575534,"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."}}