{"id":"W2035126578","doi":"10.1145/1242073.1242278","title":"The spatial bi-directional reflectance distribution function","year":2002,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bidirectional reflectance distribution function; Pixel; Representation (politics); Computer science; Reflectivity; Artificial intelligence; Point (geometry); Spatial distribution; Curse of dimensionality; Computer vision; Texture (cosmology); Function (biology); Bidirectional texture function; Surface (topology); Set (abstract data type); Normal; Directional derivative; Optics; Image texture; Image (mathematics); Remote sensing; Mathematics; Geology; Geometry; Image processing; Physics","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":[0.0001605268,0.00006739785,0.00004487655,0.00003251157,0.0004190611,0.0002373417,0.0003102154,0.00003201514,0.00003731542],"category_scores_gemma":[0.00001561341,0.00004724134,0.00004268075,0.0004391182,0.00002813374,0.000214702,0.00008171938,0.00006566737,0.00002825134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000265986,"about_ca_system_score_gemma":0.000007177363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002050723,"about_ca_topic_score_gemma":0.0000352252,"domain_scores_codex":[0.9992993,0.00004028703,0.0001363811,0.0001933025,0.0002001442,0.000130584],"domain_scores_gemma":[0.9994823,0.00005847723,0.00004893889,0.0002677195,0.0001101052,0.00003250411],"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":[0.000001502161,0.00002374116,0.0001254719,7.273084e-7,0.000004525064,2.699038e-7,0.00001736459,0.000002865574,0.00006610735,0.8969733,0.025714,0.07707009],"study_design_scores_gemma":[0.00008578475,0.0001014384,0.00294575,0.000003966624,0.000001767477,0.00000670767,0.000001389066,0.7390853,0.0017563,0.02664101,0.2292609,0.0001096836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002511476,0.0001227239,0.9942119,0.0009876098,0.0005577623,0.00007065792,0.000001046384,0.0005384198,0.003258802],"genre_scores_gemma":[0.9954704,0.0001787233,0.002742836,0.0003124718,0.000157306,0.00002278911,0.000007068666,0.000004139866,0.001104272],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9952192,"threshold_uncertainty_score":0.3223122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02111218095746667,"score_gpt":0.2616137107441839,"score_spread":0.2405015297867172,"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."}}