{"id":"W3173271410","doi":"10.1096/fasebj.2019.33.1_supplement.444.5","title":"Photogrammetry or 3D Surface Scanning – Which tool works best for anatomical specimens?","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Island Health; University of British Columbia","funders":"","keywords":"Photogrammetry; Computer science; Workflow; Laser scanning; 3d scanning; Process (computing); Scanner; Artificial intelligence; Mobile device; Computer vision; Stereoscopy; Computer graphics (images); Optics","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":[0.009009863,0.0009503053,0.001107269,0.00392812,0.0007302009,0.003009961,0.00121565,0.002828418,0.008517751],"category_scores_gemma":[0.01865619,0.0007926974,0.001304185,0.003259911,0.00430717,0.004408449,0.00198259,0.0009750633,0.005999644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006484295,"about_ca_system_score_gemma":0.001059429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078057,"about_ca_topic_score_gemma":0.002724366,"domain_scores_codex":[0.9933935,0.002576112,0.0005772666,0.001106015,0.002024104,0.0003229589],"domain_scores_gemma":[0.9886593,0.005403234,0.001212078,0.002637457,0.001817626,0.0002703778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006000648,0.0001286929,0.0408264,0.004806166,0.000306767,0.001284,0.003849759,0.005235425,0.1380628,0.01318736,0.01173519,0.7799773],"study_design_scores_gemma":[0.0001874761,0.003938546,0.1892557,0.006376836,0.001114962,0.04322535,0.01568226,0.02685838,0.3248842,0.05548203,0.3315129,0.001481245],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2003533,0.01774417,0.7141531,0.006992985,0.001372144,0.0009445091,0.002036053,0.00598205,0.05042176],"genre_scores_gemma":[0.4956586,0.008258317,0.4851948,0.001625516,0.0002372535,0.0003788203,0.0005967102,0.002024407,0.006025623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009009863,"threshold_uncertainty_score":0.04764932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313714436968842,"score_gpt":0.2442951919316788,"score_spread":0.2311580475619904,"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."}}