{"id":"W4367834888","doi":"10.1002/jemt.24338","title":"Optical profilometry for forensic bloodstain imaging","year":2023,"lang":"en","type":"article","venue":"Microscopy Research and Technique","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Profilometer; Kurtosis; Deposition (geology); Surface finish; Materials science; Surface roughness; Surface (topology); Optics; Composite material; Geology; Mathematics; Geometry; Statistics; Physics","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":[0.001172382,0.0001133155,0.0001825754,0.0003411913,0.0005941621,0.0005383047,0.0001504557,0.00004258837,0.0003012524],"category_scores_gemma":[0.0001290073,0.00008852668,0.00005698686,0.0002202473,0.0005463086,0.0001304817,0.000173181,0.0001647792,0.00005290072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003177488,"about_ca_system_score_gemma":0.00002660096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001601794,"about_ca_topic_score_gemma":0.0001182338,"domain_scores_codex":[0.998755,0.00004693132,0.0001774656,0.0002857708,0.0001904855,0.0005443249],"domain_scores_gemma":[0.9992709,0.0001528848,0.00002205664,0.0001762629,0.0002877368,0.0000901409],"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":[0.00007715551,0.00004901677,0.0002241375,0.0002764715,0.00003300729,0.00002425013,0.001328571,3.571826e-8,0.8604946,0.09188899,0.03905259,0.006551189],"study_design_scores_gemma":[0.0003501218,0.0003553134,0.00007455847,0.0001012656,0.00001834615,0.00000789532,0.00381373,0.0001081744,0.7347021,0.04441076,0.2157756,0.0002821218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739201,0.0004836236,0.001213049,0.003803742,0.000208294,0.003210927,0.000341394,0.0009251622,0.0158937],"genre_scores_gemma":[0.9790295,0.00007708989,0.005743449,0.00007087886,0.0004304829,0.001124966,0.0001144555,0.00004578491,0.01336343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.176723,"threshold_uncertainty_score":0.5190884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010395101510096,"score_gpt":0.3868286504933027,"score_spread":0.285789140342293,"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."}}