{"id":"W2981619376","doi":"10.1145/3308561.3356111","title":"Exploring Haptic Colour Identification Aids","year":2019,"lang":"en","type":"article","venue":"","topic":"Categorization, perception, and language","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Identification (biology); Computer science; Artificial intelligence; Computer vision; Plan (archaeology); Haptic technology; Perception; RGB color model; Wrist; Psychology; Medicine; Geography","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":[0.001603453,0.0008210251,0.0003258288,0.0005417967,0.0002414928,0.001505812,0.001104431,0.0009047644,0.007281674],"category_scores_gemma":[0.005216126,0.0002860381,0.0003650707,0.0002453571,0.0006966484,0.002687204,0.001809662,0.0005235259,0.0008425319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002289171,"about_ca_system_score_gemma":0.0002545602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004172517,"about_ca_topic_score_gemma":0.0004762618,"domain_scores_codex":[0.9993193,0.0002291075,0.0000352577,0.00008264776,0.0002406372,0.00009305409],"domain_scores_gemma":[0.9957401,0.003382216,0.0001257603,0.0002172213,0.0003929321,0.0001419687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002312782,0.0008001821,0.007988242,0.003936135,0.00009023097,0.002370583,0.01118547,0.004935087,0.4144973,0.01249423,0.005860503,0.5335293],"study_design_scores_gemma":[0.001361935,0.009958381,0.04930468,0.002357118,0.0007022228,0.01939585,0.02183924,0.1465286,0.4429052,0.02895666,0.2758438,0.000846197],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7972742,0.002169481,0.1778412,0.0007895136,0.0001597063,0.0003340814,0.0002070987,0.002160497,0.01906432],"genre_scores_gemma":[0.8508106,0.0008247686,0.1396135,0.000303858,0.0000287517,0.0001662635,0.0001334411,0.0001157333,0.008003063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007281674,"threshold_uncertainty_score":0.02435958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0808003037579799,"score_gpt":0.3120257430521302,"score_spread":0.2312254392941503,"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."}}