{"id":"W2056849512","doi":"10.1068/b36022","title":"Movement Surface: A Multilevel Approach for Predicting Visitor Movement in Nature Areas","year":2011,"lang":"en","type":"article","venue":"Environment and Planning B Planning and Design","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Visitor pattern; Movement (music); Recreation; Destinations; Computer science; Motion (physics); Tourism; Geography; Artificial intelligence; Ecology","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":[0.001114634,0.0001858338,0.0002100543,0.00005807794,0.0004460208,0.00006188273,0.0001148746,0.0002070371,0.00002460304],"category_scores_gemma":[0.00003406606,0.0001728187,0.00003258978,0.00004954133,0.0001214155,0.00018472,0.00002791697,0.0002467862,5.118804e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004671053,"about_ca_system_score_gemma":0.00002822004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003504754,"about_ca_topic_score_gemma":0.00000386372,"domain_scores_codex":[0.9986038,0.00009392828,0.0002469251,0.0004348102,0.0002372258,0.0003833115],"domain_scores_gemma":[0.9994656,0.0001839836,0.00009759678,0.0001064482,0.000007672387,0.0001387039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001741543,0.0001058994,0.9690558,0.00003507364,0.00002358086,0.00001041244,0.02752079,0.001994016,0.0001311382,0.0001096913,0.0001982286,0.0006412078],"study_design_scores_gemma":[0.001204254,0.0001632874,0.9682593,0.0001506241,0.0000437313,2.817736e-7,0.009714616,0.01738469,0.0005309421,0.001319084,0.0008148727,0.0004143645],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930433,0.00233367,0.06384886,0.00003335454,0.0001208274,0.0008256052,0.00002239695,0.00005756385,0.002324682],"genre_scores_gemma":[0.9726384,0.00003594163,0.02664228,0.0001393856,0.0001259338,0.00004832002,0.00002901073,0.00001337163,0.0003273946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04220532,"threshold_uncertainty_score":0.7047341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05311024654486168,"score_gpt":0.2734832957348644,"score_spread":0.2203730491900027,"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."}}