{"id":"W753039143","doi":"","title":"DEVELOPMENT OF A DIGITAL PAIN MAPPING TOOL USING ICONOGRAPHY FOR THE ASSESSMENT OF SENSORY PAIN","year":2014,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Arthritis Network; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Arthritis Society","keywords":"Iconography; Sensory system; Medicine; Pain management; Pain assessment; Psychology; Cartography; Physical therapy; Neuroscience; Art; Geography; Visual arts","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00399883,0.00110932,0.0006235378,0.002331791,0.0005546593,0.002467682,0.001810404,0.00109062,0.0132913],"category_scores_gemma":[0.009605655,0.0005769534,0.001094848,0.0009118253,0.0008475318,0.002246975,0.001753805,0.001449084,0.003979634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004715552,"about_ca_system_score_gemma":0.002378765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001159613,"about_ca_topic_score_gemma":0.001743058,"domain_scores_codex":[0.9975739,0.0005952415,0.0002078214,0.000281007,0.001221508,0.000120439],"domain_scores_gemma":[0.9952762,0.002221537,0.0002145818,0.0003277826,0.001714104,0.000245733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002910772,0.0005307926,0.004352723,0.002322852,0.00005299292,0.0008362131,0.004708916,0.00267917,0.07709362,0.006100542,0.01821607,0.8828151],"study_design_scores_gemma":[0.0006859833,0.006453002,0.03406772,0.005711664,0.0005163359,0.009490787,0.008577147,0.0697309,0.2053133,0.01112967,0.6473955,0.0009280797],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06158064,0.00125987,0.8930943,0.001545446,0.0009318732,0.007447443,0.000994981,0.007380384,0.02576492],"genre_scores_gemma":[0.05622464,0.00111007,0.9287589,0.0004655797,0.00008166322,0.002785482,0.0005529342,0.0005375974,0.009483133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0132913,"threshold_uncertainty_score":0.04446381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03746549909904497,"score_gpt":0.2414014478533175,"score_spread":0.2039359487542725,"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."}}