{"id":"W2710002000","doi":"","title":"REVERSE SUBDIVISION FOR OPTIMIZING VISIBILITY TESTS","year":2018,"lang":"en","type":"article","venue":"International Conference on Computer Graphics Theory and Applications","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Terrain; Visibility; Computer science; Subdivision; Computation; Set (abstract data type); Computer vision; Algorithm; Artificial intelligence; Geography","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":[0.0004670115,0.0001149997,0.00008596507,0.00005471078,0.0003532412,0.00008613805,0.0002769103,0.00005563915,0.000187908],"category_scores_gemma":[0.00002137468,0.000107606,0.00004985993,0.0001458428,0.0004095962,0.00009583148,0.0001149469,0.00009904054,0.0001116641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002811052,"about_ca_system_score_gemma":0.000009508019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001678501,"about_ca_topic_score_gemma":0.00001609589,"domain_scores_codex":[0.9990763,0.00005079885,0.0001746807,0.000415034,0.00015253,0.0001306346],"domain_scores_gemma":[0.9991975,0.0002501523,0.00007846302,0.0003053147,0.00009014038,0.00007844213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003590198,0.00007980737,0.0002806135,0.000002183888,0.00001099574,1.024605e-7,0.0001098279,0.00002220831,0.0009980551,0.9509859,0.0008029592,0.04667144],"study_design_scores_gemma":[0.0004511142,0.0002219648,0.009574398,0.00003907541,0.0000221946,0.00001161457,0.00006788601,0.1245039,0.001255971,0.7635822,0.09993593,0.0003337174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04839807,0.00000347544,0.9302476,0.001009854,0.0001389721,0.0005427841,0.00003909987,0.00008308835,0.01953705],"genre_scores_gemma":[0.9826615,0.00002216492,0.01581354,0.0008814986,0.0002632751,0.00006183641,0.00003737956,0.000009884027,0.0002489476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9342634,"threshold_uncertainty_score":0.4388044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.027284051415511,"score_gpt":0.3038126417219419,"score_spread":0.276528590306431,"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."}}