{"id":"W4212973017","doi":"10.1002/cpz1.369","title":"Post‐Stroke Hemiplegic Rodent Evaluation: A Framework for Assessing Forelimb Movement Quality Using Kinematics","year":2022,"lang":"en","type":"article","venue":"Current Protocols","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Forelimb; Kinematics; Physical medicine and rehabilitation; Stroke (engine); Computer science; Work (physics); Neuroscience; Psychology; Medicine; Engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002136033,0.0002065586,0.0004287717,0.0001702676,0.0003857322,0.00008939371,0.0001401418,0.00006682717,0.0007002067],"category_scores_gemma":[0.001325355,0.0001876279,0.0003735453,0.0002224256,0.00004647366,0.0001334797,0.0001306752,0.0003900748,0.000004542914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008135795,"about_ca_system_score_gemma":0.0005868383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004593976,"about_ca_topic_score_gemma":4.417931e-7,"domain_scores_codex":[0.9970031,0.0002834329,0.0007687203,0.0003966165,0.00122002,0.0003280561],"domain_scores_gemma":[0.9979342,0.0004828662,0.0004245016,0.0004780038,0.0005429196,0.0001375264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006549741,0.01922628,0.2924066,0.03876652,0.00119933,0.00001492282,0.009141914,0.02509565,0.1184123,0.06797712,0.006099326,0.4151103],"study_design_scores_gemma":[0.05248147,0.01236534,0.1077427,0.01450379,0.002405094,0.0001394879,0.02434867,0.3973897,0.01846239,0.1042849,0.261967,0.003909409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.4363766,0.0006255078,0.1710205,0.001457241,0.002188166,0.3873108,0.0002999827,0.0001723455,0.0005488088],"genre_scores_gemma":[0.1689381,0.000004103794,0.1067794,0.001028287,0.001081849,0.7215379,0.0002688026,0.00008174031,0.0002798486],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.4112009,"threshold_uncertainty_score":0.7666773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2072613463204715,"score_gpt":0.506077776956597,"score_spread":0.2988164306361254,"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."}}