{"id":"W3107807409","doi":"10.1186/s12938-020-00839-3","title":"3-Dimensional printing in rehabilitation: feasibility of printing an upper extremity gross motor function assessment tool","year":2021,"lang":"en","type":"article","venue":"BioMedical Engineering OnLine","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Rehabilitation; Test (biology); Physical medicine and rehabilitation; Function (biology); Computer science; Margin (machine learning); Physical therapy; Medicine; Medical physics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008075157,0.0001582526,0.000393538,0.0002258558,0.00002870315,0.000009769076,0.00005591424,0.0001686739,0.0002115499],"category_scores_gemma":[0.002705605,0.0001441264,0.000172001,0.000498969,0.00009337055,0.0001219372,0.0000690064,0.0003550502,0.000002025556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002476047,"about_ca_system_score_gemma":0.0003307255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001410292,"about_ca_topic_score_gemma":0.00000446291,"domain_scores_codex":[0.9980114,0.00007465892,0.0007229598,0.0004143731,0.0005330289,0.0002435795],"domain_scores_gemma":[0.9986174,0.0005188686,0.00009047138,0.0003358353,0.0002598298,0.0001775926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001724426,0.003269744,0.7052255,0.001261392,0.00006247187,0.00002631408,0.000161561,0.0009280039,0.2765046,0.0005488631,0.00003792119,0.01180121],"study_design_scores_gemma":[0.001494446,0.0003761468,0.9510162,0.0004227033,0.00002416584,0.00002358768,0.0002073543,0.04469301,0.0004151977,0.00003094656,0.001166372,0.0001298205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925365,0.00009597396,0.005260997,0.001057919,0.0005870732,0.0003260402,0.00002454479,0.00008847725,0.00002242949],"genre_scores_gemma":[0.8688321,0.000004237235,0.1305595,0.00006589648,0.0002543459,0.00001574643,0.0001865544,0.00001854783,0.00006309322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2760894,"threshold_uncertainty_score":0.5877302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735460084437575,"score_gpt":0.3094250727467269,"score_spread":0.2920704719023511,"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."}}