{"id":"W7070028909","doi":"","title":"Optimizing MediaPipe for the assessment of hand trajectories using a touchscreen shape-tracing task","year":2023,"lang":"en","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Touchscreen; CLIPS; Mean squared error; Interpolation (computer graphics); Pipeline (software); Task (project management)","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":[0.001688684,0.001047688,0.0006262496,0.0007866818,0.0002514693,0.001033654,0.001100823,0.0008955051,0.005322849],"category_scores_gemma":[0.01024773,0.0005593584,0.0004549205,0.0003715067,0.0003132931,0.001290023,0.001260199,0.0005747917,0.001580012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002916747,"about_ca_system_score_gemma":0.0006767961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001496346,"about_ca_topic_score_gemma":0.002980379,"domain_scores_codex":[0.9993548,0.00008751226,0.00006384315,0.0002329513,0.0001942674,0.00006664988],"domain_scores_gemma":[0.9975646,0.001383503,0.0002068534,0.0001947995,0.000532541,0.0001178206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004609603,0.00069891,0.01029076,0.001575048,0.0001925048,0.0004007788,0.0006794488,0.009656113,0.5563349,0.0007285796,0.00431451,0.4105189],"study_design_scores_gemma":[0.0008892426,0.007033076,0.2187348,0.0003023197,0.0004808862,0.001943201,0.0005892575,0.3080795,0.4435545,0.002884411,0.015077,0.0004317346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4325287,0.000587691,0.5508653,0.0001480825,0.0001528141,0.002092233,0.001501174,0.009948593,0.002175393],"genre_scores_gemma":[0.4755488,0.000404296,0.514097,0.0002369173,0.00004440194,0.003353831,0.002031011,0.001031142,0.003252725],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005322849,"threshold_uncertainty_score":0.01780671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2529044648386455,"score_gpt":0.4521864909667838,"score_spread":0.1992820261281382,"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."}}