{"id":"W4385161899","doi":"10.3390/f14071491","title":"How Vegetation Colorization Design Affects Urban Forest Aesthetic Preference and Visual Attention: An Eye-Tracking Study","year":2023,"lang":"en","type":"article","venue":"Forests","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fujian University of Technology; Department of Education, Fujian Province","keywords":"Landscaping; Perception; Urban forestry; Homogeneous; Eye tracking; Vegetation (pathology); Preference; Urban forest; Canopy; Eye movement; Computer science; Cognitive psychology; Psychology; Geography; Forestry; Ecology; Computer vision; Artificial intelligence; Mathematics; Medicine; Statistics; 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":[0.001090874,0.0002484391,0.0002228857,0.0004316618,0.00029367,0.0006059339,0.0002120436,0.0003976304,0.002173627],"category_scores_gemma":[0.005071094,0.0001642869,0.0004160485,0.0002457879,0.0002986629,0.0005560484,0.0003991416,0.0003774421,0.000210324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003277949,"about_ca_system_score_gemma":0.0002808759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004178286,"about_ca_topic_score_gemma":0.006425755,"domain_scores_codex":[0.9994468,0.0001629941,0.00003947431,0.000126924,0.0001377459,0.00008603928],"domain_scores_gemma":[0.9972994,0.001300686,0.0006442552,0.0001463204,0.0004567872,0.0001526322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002063069,0.002583159,0.8262407,0.000705378,0.000263387,0.000642182,0.02926068,0.0006848726,0.05525384,0.0004652883,0.001464442,0.08037304],"study_design_scores_gemma":[0.00003225465,0.0009356213,0.9907545,0.00004125658,0.0001103236,0.0001947716,0.003912852,0.001207076,0.001789663,0.0001417913,0.000849485,0.00003043558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988813,0.00006587477,0.0002608473,0.0000179584,0.00000260274,0.00002238032,0.00003273426,0.000003712862,0.0007126903],"genre_scores_gemma":[0.9986976,0.00007030132,0.0003943891,0.00004018225,0.000004314259,0.00004842571,0.00004627777,0.000003513682,0.0006950433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004178286,"threshold_uncertainty_score":0.008307934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04443464771352616,"score_gpt":0.2985569921456089,"score_spread":0.2541223444320828,"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."}}