{"id":"W6926303776","doi":"10.24433/co.0174131.v2","title":"3D Model Watermarking Using Surface Integrals of Generated Random Vector Fields","year":2023,"lang":"en","type":"other","venue":"Code Ocean","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Digital watermarking; Watermark; Robustness (evolution); Random field; Invariant (physics); Conditional random field; Surface (topology); Multivariate random variable; Euclidean 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":[],"consensus_categories":[],"category_scores_codex":[0.00019033,0.0002628679,0.0006908855,0.0001422798,0.00003064003,0.00001405071,0.0001304238,0.0003931491,0.0005996756],"category_scores_gemma":[0.0001247239,0.0001825898,0.0001436318,0.0001764787,0.00005949986,0.0000197875,0.00006163902,0.00028062,0.00001854015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004505568,"about_ca_system_score_gemma":0.00008708544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003522967,"about_ca_topic_score_gemma":0.0001075865,"domain_scores_codex":[0.9989073,0.00004047324,0.0003027186,0.0003456088,0.0001642807,0.0002396204],"domain_scores_gemma":[0.9992689,0.00003521366,0.0001870009,0.0003574134,0.00008345267,0.00006805134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004245265,0.00006956517,0.000103356,0.0008921649,0.0004705293,0.00005620541,0.0001901864,0.0009190086,0.3012166,0.00001649397,0.693581,0.002060272],"study_design_scores_gemma":[0.006182416,0.0001920259,0.00002492074,0.008781931,0.001686209,0.00006740167,0.00006001773,0.2041305,0.6131392,0.00004809626,0.1641555,0.001531766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.856168,0.01176514,0.002233463,0.00334897,0.005332565,0.004449228,0.001797241,0.003022355,0.111883],"genre_scores_gemma":[0.4290991,0.0007230845,0.004425177,0.0002070483,0.0007132632,1.796797e-7,0.00009911227,0.0008493235,0.5638837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5294255,"threshold_uncertainty_score":0.7445796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04071924180872846,"score_gpt":0.2789237087997163,"score_spread":0.2382044669909878,"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."}}