{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003984458,0.0001176281,0.0002553686,0.0002338527,0.0003780549,0.00001916588,0.0003577828,0.0001488719,0.002024437],"category_scores_gemma":[0.0003137611,0.0001194713,0.0001267654,0.0005140523,0.0007347325,0.0003070569,0.0000997743,0.0001702059,0.0001010325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000431833,"about_ca_system_score_gemma":0.0003277478,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01695561,"about_ca_topic_score_gemma":0.001267159,"domain_scores_codex":[0.9982358,0.0001477115,0.0003001507,0.0002324528,0.000759983,0.000323948],"domain_scores_gemma":[0.9987863,0.0001544405,0.0001848548,0.0002843442,0.0004437286,0.0001462964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009742698,0.004113693,0.1587422,0.0002432044,0.0007512055,0.001425173,0.04482004,0.1215437,0.002215983,0.005372736,0.6337224,0.02607546],"study_design_scores_gemma":[0.02623182,0.00663654,0.3344475,0.0009607141,0.001270974,0.00009427513,0.06652336,0.106938,0.04355801,0.0058163,0.4012423,0.006280156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.686967,0.0002010409,0.01402535,0.001864927,0.0009369986,0.0006701862,0.0001042075,0.000134789,0.2950955],"genre_scores_gemma":[0.9816198,0.0003216333,0.002329646,0.0000261174,0.0006380665,0.00000663119,0.00002614085,0.00001626104,0.01501568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2946528,"threshold_uncertainty_score":0.9988878,"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."}}