{"id":"W4255619212","doi":"10.31234/osf.io/yejg8","title":"Deciphering landscape preferences: Investigating the roles of familiarity and biome types","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Biome; Swamp; Marsh; Geography; Natural (archaeology); Ecology; Preference; Psychology; Ecosystem; Wetland; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001514881,0.0001806596,0.00036108,0.0007223289,0.0004062657,0.0009072428,0.0003324629,0.0002804529,0.002441725],"category_scores_gemma":[0.006607126,0.0001409618,0.0002570986,0.0005481604,0.0006439292,0.001372169,0.0006304426,0.0002932993,0.0002038775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004505116,"about_ca_system_score_gemma":0.0003069882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02488535,"about_ca_topic_score_gemma":0.06999046,"domain_scores_codex":[0.9994356,0.0001549625,0.00004196953,0.0001390375,0.0001434293,0.00008503343],"domain_scores_gemma":[0.996077,0.001529192,0.001132476,0.0003462141,0.0005937011,0.0003213778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003366793,0.00008511247,0.9670407,0.00009570839,0.0000886726,0.00009093259,0.005175709,0.0001021702,0.00895967,0.0001051652,0.0001466171,0.0177728],"study_design_scores_gemma":[0.00000265248,0.0001071689,0.9974644,0.000006785719,0.00001273361,0.00005607211,0.001545453,0.0002308985,0.0003435855,0.00007191554,0.0001536212,0.000004630973],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988213,0.00006843866,0.0003781565,0.00001836455,0.000001300858,0.000007629866,0.00004191395,0.00000198972,0.0006607865],"genre_scores_gemma":[0.9993706,0.00003606194,0.0003366265,0.00001193835,0.000001801303,0.000007736722,0.00004978413,0.000001878799,0.0001835361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02488535,"threshold_uncertainty_score":0.04948103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.036839209168335,"score_gpt":0.2580277369991147,"score_spread":0.2211885278307797,"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."}}