{"id":"W2380860301","doi":"","title":"Spatial Optimization of Landscape Tourism Functions of Yellow River Custom Tourist Line","year":2008,"lang":"en","type":"article","venue":"Anhui nongye kexue","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Tourism; Recreation; Line (geometry); Geography; Regional science; Computer science; Business; Environmental planning; Mathematics; Ecology; 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":[0.0003226222,0.000380956,0.0002762411,0.0004059944,0.0001938108,0.0004668065,0.0002486129,0.0002691715,0.001226547],"category_scores_gemma":[0.0006312296,0.0001421612,0.0003725867,0.0003486722,0.0001955766,0.000303039,0.0003239071,0.0001566854,0.00006940559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005933781,"about_ca_system_score_gemma":0.0004276196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00959307,"about_ca_topic_score_gemma":0.006598174,"domain_scores_codex":[0.9999129,0.00003050963,0.000003469354,0.00001342522,0.00001374427,0.00002607386],"domain_scores_gemma":[0.9998733,0.00004929616,0.00001698242,0.000006391963,0.00004109133,0.00001291144],"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":[0.0000732035,0.00002813405,0.00288836,0.00004014669,0.00001839963,0.00007913126,0.00004761962,0.9755514,0.003283026,0.002968014,0.0005473346,0.01447529],"study_design_scores_gemma":[0.000004634158,0.00003823804,0.001522035,0.000002197032,0.000006072914,0.0000129611,0.00005920211,0.9969976,0.000493305,0.0006373591,0.0002229071,0.000003451274],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8268265,0.0002859726,0.1622633,0.0001857698,0.00001721975,0.00004009833,0.0001253558,0.00008429596,0.01017149],"genre_scores_gemma":[0.9893256,0.00008436501,0.008770641,0.000007515628,0.00000270323,0.00002504027,0.0000591018,0.00001505947,0.001709991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00959307,"threshold_uncertainty_score":0.01907444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02595217810534367,"score_gpt":0.2860678268569232,"score_spread":0.2601156487515795,"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."}}