{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006760242,0.000576739,0.0005362575,0.0008072166,0.0002804379,0.0009380825,0.0007964741,0.0007010942,0.00104817],"category_scores_gemma":[0.00227509,0.0002942569,0.0005895416,0.0005849241,0.0009082248,0.001652541,0.001107653,0.0006495023,0.000426272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706557,"about_ca_system_score_gemma":0.000369925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005958836,"about_ca_topic_score_gemma":0.0004773276,"domain_scores_codex":[0.9994831,0.00007966293,0.0000232081,0.00008506829,0.0002944586,0.00003452816],"domain_scores_gemma":[0.9991934,0.0002121575,0.0002014724,0.0002504699,0.0001157124,0.00002693958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003707796,0.00007364573,0.0009818784,0.0001099749,0.00006058775,0.0002519259,0.0001599139,0.3648657,0.2286894,0.07098512,0.001117349,0.3323337],"study_design_scores_gemma":[0.00001215099,0.00008525803,0.0002055186,0.000007076627,0.000008531663,0.0001293199,0.000009915059,0.9475759,0.04307882,0.007238406,0.001627704,0.0000213416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01990393,0.0001145055,0.9786462,0.00005756346,0.00002118985,0.00001630339,0.00001789198,0.0004873258,0.0007351359],"genre_scores_gemma":[0.5234466,0.0003077681,0.4736674,0.00005573377,0.00004537774,0.00004620791,0.0001458598,0.0001763256,0.002108696],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.00104817,"threshold_uncertainty_score":0.003575206,"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."}}