{"id":"W3046625800","doi":"10.1007/978-3-030-54407-2_1","title":"Fused Geometry Augmented Images for Analyzing Textured Mesh","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face recognition and analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Discriminative model; Pattern recognition (psychology); Feature (linguistics); Representation (politics); Convolutional neural network; Feature vector; Inverse; Computer vision; Mathematics; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006422222,0.0005630955,0.0007510713,0.001363913,0.0003210446,0.0008515275,0.002836646,0.0002783985,0.0000591505],"category_scores_gemma":[0.0002179332,0.0005165507,0.0004015675,0.001533047,0.0003663317,0.0005687533,0.000881374,0.0006231758,0.00007690543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002091203,"about_ca_system_score_gemma":0.0003584089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001023959,"about_ca_topic_score_gemma":0.00001668419,"domain_scores_codex":[0.9960986,0.00003396288,0.0005853263,0.001795931,0.0008379138,0.0006482167],"domain_scores_gemma":[0.9976234,0.0004187694,0.0003478015,0.0009575612,0.0003686041,0.0002838333],"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":[0.00001087809,0.00003846447,0.00003241618,0.00009868643,0.00009486487,0.00006153653,0.0002777829,0.005090469,0.001562548,0.005896054,0.0003794316,0.9864569],"study_design_scores_gemma":[0.0008309385,0.000232262,0.00006377147,0.0003962313,0.00007502099,0.00002642231,5.25764e-7,0.9086218,0.009634107,0.07479896,0.004081593,0.001238361],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001609305,0.0004617648,0.9938722,0.003154259,0.0007757918,0.0004318722,0.00003109128,0.0002569557,0.0009999946],"genre_scores_gemma":[0.1120426,0.0001427034,0.8795639,0.006123176,0.0008180586,0.00003622232,0.00006995752,0.00007848319,0.001124887],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9852185,"threshold_uncertainty_score":0.9997286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846768682624359,"score_gpt":0.2521398499695575,"score_spread":0.2336721631433139,"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."}}