{"id":"W6925120487","doi":"10.17605/osf.io/mjk8a","title":"Wayfinding in Healthcare Settings: How Windows and Signage Impact Route Choices","year":2024,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Art, Technology, and Culture","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Signage; Window (computing); Health care; Natural (archaeology); Trajectory; Key (lock)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009991656,0.000200244,0.0001861379,0.0004742953,0.0007514632,0.002538042,0.0002441748,0.000390312,0.002677246],"category_scores_gemma":[0.009181939,0.0001380853,0.0002422065,0.0003555647,0.001439068,0.0008328223,0.001499106,0.0003847879,0.0001734363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007110114,"about_ca_system_score_gemma":0.001365167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01928092,"about_ca_topic_score_gemma":0.0403696,"domain_scores_codex":[0.9987261,0.0007288299,0.0000552809,0.0001242716,0.0001953883,0.0001701572],"domain_scores_gemma":[0.9955583,0.00276095,0.0009032459,0.0001476294,0.0002181224,0.0004116776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006813694,0.0004410777,0.8145244,0.0002417246,0.0001321867,0.0007464209,0.09365292,0.0009161371,0.006260849,0.001151733,0.0006604043,0.08059076],"study_design_scores_gemma":[0.00002348546,0.0006743813,0.852949,0.0001530824,0.00008689013,0.0004292729,0.1392194,0.0009504282,0.0009874015,0.001018911,0.003457658,0.00005013042],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9975092,0.0001229789,0.0002745758,0.00009886351,0.000003973162,0.000005563881,0.0000159742,0.000002590336,0.00196635],"genre_scores_gemma":[0.9992878,0.0001133932,0.0002794237,0.0000216838,0.000001342893,0.000004085631,0.000009081985,0.00000205895,0.0002812443],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01928092,"threshold_uncertainty_score":0.03833735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109653871671267,"score_gpt":0.3235981505707983,"score_spread":0.2925016118540856,"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."}}