{"id":"W3170621966","doi":"10.82308/44646","title":"Large-scale simulation of an interactive deformable terrain","year":2020,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Terrain; Scale (ratio); Computer science; Computer graphics (images); Artificial intelligence; Computer vision; Geology; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005517607,0.0002557417,0.0003187844,0.0002250207,0.0003666369,0.0001134796,0.001047288,0.0001361223,0.00003262249],"category_scores_gemma":[0.0001317113,0.000263823,0.0001526394,0.0009593972,0.00003421738,0.002728894,0.0006258019,0.000346871,0.00002201718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009087136,"about_ca_system_score_gemma":0.00002036734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003639647,"about_ca_topic_score_gemma":0.00003921921,"domain_scores_codex":[0.9977825,0.0002386244,0.0005558109,0.0006334832,0.0004326256,0.0003570157],"domain_scores_gemma":[0.9983619,0.0001162298,0.0003131408,0.0005958112,0.0003319322,0.0002809681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000835797,0.0005658374,0.000155331,0.000109096,0.00007839774,0.00002033977,0.0005308079,0.006021108,0.01662243,0.8588383,0.000007577763,0.1169672],"study_design_scores_gemma":[0.0005290525,0.0004699852,0.0002743948,0.00004772731,0.00001120193,0.000005547613,0.00007564198,0.822049,0.1288958,0.03237043,0.01491091,0.0003603993],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8704913,0.00002600994,0.1213851,0.0001008412,0.0003021629,0.0005589692,0.000215515,0.001138367,0.005781731],"genre_scores_gemma":[0.9855545,0.000009059188,0.01321761,0.001102639,0.00002332128,0.00001606375,0.00002341191,0.00003009082,0.00002331233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8264678,"threshold_uncertainty_score":0.9999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02175758438732305,"score_gpt":0.2800665592325073,"score_spread":0.2583089748451843,"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."}}