{"id":"W1916480773","doi":"10.3109/17453054.2013.851654","title":"The identification of tattoo designs under cover-up tattoos using digital infrared photography","year":2013,"lang":"en","type":"article","venue":"Journal of Visual Communication in Medicine","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Photography; Cover (algebra); Visibility; Visual arts; Art; Computer science; Geography; Engineering","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":[0.001321583,0.0002496149,0.0002110816,0.002682489,0.0006618898,0.000685317,0.0002420751,0.0003903081,0.002066881],"category_scores_gemma":[0.004153618,0.0002782224,0.00035864,0.0008094928,0.0007844405,0.0007870616,0.0007666547,0.0003691553,0.0004625167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000345597,"about_ca_system_score_gemma":0.0002483515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006126842,"about_ca_topic_score_gemma":0.001491642,"domain_scores_codex":[0.9986116,0.0003677848,0.0001004619,0.0001544577,0.0006514466,0.0001143071],"domain_scores_gemma":[0.997014,0.001291664,0.0006158933,0.0005307355,0.0004803197,0.00006739535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001280854,0.000178373,0.1928098,0.001027881,0.0001254105,0.002226607,0.01461549,0.001097242,0.4667142,0.002556261,0.000912601,0.3164552],"study_design_scores_gemma":[0.00002405016,0.001707834,0.6692616,0.0003815874,0.0002522781,0.01840774,0.01019764,0.003960511,0.272645,0.001365765,0.02164059,0.0001555008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791325,0.001395027,0.01301922,0.00005159054,0.00003604672,0.0001089763,0.00005258766,0.00004805613,0.006155988],"genre_scores_gemma":[0.9725697,0.0007402289,0.0229865,0.0000374614,0.00001487631,0.00003792739,0.00004793896,0.00002174803,0.003543688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002682489,"threshold_uncertainty_score":0.0069893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09158985909693644,"score_gpt":0.3369925674561984,"score_spread":0.2454027083592619,"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."}}