{"id":"W4409744797","doi":"10.2139/ssrn.5229826","title":"Transfer Learning on Sam for Footwear Outsole Segmentation","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Segmentation; Transfer of learning; Artificial intelligence; Computer science; Psychology","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001020301,0.0002117519,0.0002129943,0.0002886161,0.0003709656,0.0002893956,0.0005172428,0.0001752697,0.00001531663],"category_scores_gemma":[0.00002740396,0.0002088914,0.0002702599,0.0001043964,0.00001127993,0.0002775355,0.00007557633,0.003220642,0.00002688419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007851464,"about_ca_system_score_gemma":0.001783919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009985955,"about_ca_topic_score_gemma":0.00005922554,"domain_scores_codex":[0.997775,0.0001285972,0.0003176624,0.0003891568,0.0002650178,0.001124601],"domain_scores_gemma":[0.9994041,0.00008358114,0.0001283358,0.000188763,0.0001405417,0.00005465912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009826056,0.0001639096,0.00003509642,0.0001047589,0.0004405017,0.000002387235,0.0008225347,0.01386958,0.0007801623,0.2945818,0.0004094962,0.6886916],"study_design_scores_gemma":[0.002259491,0.001620317,0.00006045403,0.0004816407,0.0001551162,0.00009185784,0.000891973,0.02161097,0.009499151,0.947804,0.01475779,0.0007671859],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01681563,0.0003310189,0.9787292,0.001354085,0.000967678,0.00037315,0.000006775274,0.0001165866,0.001305841],"genre_scores_gemma":[0.9723097,0.004430543,0.004629935,0.001045809,0.001301087,0.000172596,0.0001106049,0.00004222597,0.01595748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9740993,"threshold_uncertainty_score":0.999079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01728437883654594,"score_gpt":0.2795764304776452,"score_spread":0.2622920516410993,"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."}}