{"id":"W2247339341","doi":"10.32920/ryerson.14636172.v1","title":"A multi-dasymetric mapping approach for tourism","year":2021,"lang":"en","type":"article","venue":"","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Tourism; Land cover; Geography; Distribution (mathematics); Weighting; Cartography; Census; Land use; Regional science; Civil engineering; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003239114,0.0005266056,0.0003447495,0.002173075,0.0004194763,0.001875568,0.0007958857,0.0003591894,0.00506088],"category_scores_gemma":[0.001103697,0.0002855422,0.0007412777,0.003164371,0.0002457324,0.0007095896,0.001536418,0.0005094043,0.001867327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005925459,"about_ca_system_score_gemma":0.0008259416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055361,"about_ca_topic_score_gemma":0.01430277,"domain_scores_codex":[0.9996496,0.00007238222,0.00002565342,0.00009354743,0.0001297637,0.00002900345],"domain_scores_gemma":[0.9998017,0.00003328474,0.00002599948,0.00004138484,0.00008339072,0.00001418707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006348789,0.0001062826,0.01318253,0.0006427387,0.0001541815,0.0005245674,0.00187984,0.1258639,0.02052587,0.07116913,0.02344116,0.7424463],"study_design_scores_gemma":[0.0000207134,0.0001194999,0.0380003,0.0001466346,0.00006530654,0.0009192456,0.003059502,0.7373503,0.006432584,0.04863062,0.1651223,0.0001329451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01270053,0.000171796,0.9742517,0.0001751162,0.00006000529,0.0002092306,0.002576205,0.001390409,0.008465057],"genre_scores_gemma":[0.12831,0.0003891266,0.8604963,0.00005084413,0.00003514894,0.0003944313,0.003473971,0.0003083814,0.006541822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01055361,"threshold_uncertainty_score":0.02098435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1163938330139666,"score_gpt":0.3708145151031707,"score_spread":0.2544206820892041,"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."}}