{"id":"W4396796398","doi":"10.3390/biomedinformatics4020069","title":"A Smartphone-Based Algorithm for L Test Subtask Segmentation","year":2024,"lang":"en","type":"article","venue":"BioMedInformatics","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Test (biology); Artificial intelligence; Segmentation; Algorithm; Computer vision; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003586448,0.0001174851,0.00009872729,0.0002527293,0.00008913308,0.0003991488,0.0003646731,0.00005800403,0.000002758499],"category_scores_gemma":[0.0001526837,0.0001003361,0.00006215349,0.000527343,0.00003400934,0.0004869855,0.00005723387,0.00006127695,0.00005271443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006629268,"about_ca_system_score_gemma":0.0001316679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005758581,"about_ca_topic_score_gemma":2.260931e-7,"domain_scores_codex":[0.9991511,0.000005765723,0.0002680349,0.0001374123,0.0002227118,0.0002149703],"domain_scores_gemma":[0.9987586,0.0007716138,0.00005520068,0.0002665101,0.00007858556,0.00006946417],"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":[4.636906e-7,0.00002303124,0.0000392845,0.0001668484,0.000006830466,0.000002525065,0.0005689206,0.000001678572,0.000108506,0.0004317296,0.06482736,0.9338228],"study_design_scores_gemma":[0.0001598388,0.0001587492,0.00003763901,0.000105121,0.00000769832,0.00001361309,0.000008963433,0.9745041,0.003714281,0.005628816,0.01551668,0.0001444847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001036073,0.0001023325,0.988897,0.0004107697,0.0006770232,0.0002574729,0.00003930546,0.009371736,0.0001407263],"genre_scores_gemma":[0.005627581,0.000005962392,0.9936109,0.0004087124,0.00009253738,0.0001072913,0.00005358662,0.00001084598,0.00008265148],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9745024,"threshold_uncertainty_score":0.4091587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01916356167432356,"score_gpt":0.2809780010925949,"score_spread":0.2618144394182713,"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."}}