{"id":"W4319599285","doi":"10.2352/cic.2022.30.1.23","title":"A 360° Omnidirectional Photometer using a Ricoh Theta Z1","year":2022,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Luminance; Photometer; Omnidirectional antenna; Computer vision; Computer science; Calibration; Optics; Artificial intelligence; Computer graphics (images); Metre; Remote sensing; Physics; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003494827,0.0001462122,0.0001492053,0.0001763138,0.0004809564,0.0003096736,0.0005790259,0.00001441423,0.0002696315],"category_scores_gemma":[0.00003066025,0.0001505741,0.00004230333,0.0003656033,0.00009228298,0.0005261524,0.0008594558,0.0002097256,0.000009656774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000885295,"about_ca_system_score_gemma":0.0001322126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008751371,"about_ca_topic_score_gemma":0.00000307251,"domain_scores_codex":[0.9987014,0.0001115886,0.0001684608,0.0004369194,0.0002974458,0.0002842088],"domain_scores_gemma":[0.9993459,0.0000627695,0.00008406607,0.0003445534,0.0001023481,0.00006037326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001327715,0.0006215554,0.01758492,0.00009732459,0.0001199522,0.0001238675,0.006979209,0.00009312362,0.7519572,0.05114815,0.01366556,0.1574764],"study_design_scores_gemma":[0.001694059,0.0002735645,0.006645855,0.00008203552,0.00005146465,0.0008381187,0.0002409871,0.7330779,0.04269657,0.02141415,0.1915952,0.001390189],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1618162,0.0003226513,0.8284672,0.0007737702,0.0005092236,0.0002825183,0.000009237311,0.0004536983,0.007365413],"genre_scores_gemma":[0.9484537,0.00001452826,0.04974042,0.0007324085,0.00003070729,0.00009276568,0.00000336294,0.00000974019,0.0009223641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7866375,"threshold_uncertainty_score":0.6140231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0383423169572753,"score_gpt":0.2800574390001231,"score_spread":0.2417151220428478,"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."}}