{"id":"W2042277556","doi":"10.1889/1.3069820","title":"59.2: Defining Dynamic Range","year":2008,"lang":"en","type":"article","venue":"SID Symposium Digest of Technical Papers","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dolby (Canada)","funders":"","keywords":"Luminance; Range (aeronautics); High dynamic range; Metric (unit); Dynamic range; Computer science; Computer graphics (images); Computer vision; Perception; Artificial intelligence; Mathematics; Engineering; Psychology; Operations management; Aerospace engineering","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":[0.002083691,0.001040761,0.0007711591,0.003000355,0.0008337867,0.004899537,0.001438163,0.001431958,0.008225363],"category_scores_gemma":[0.008753081,0.0004538939,0.0009156255,0.001972371,0.0034346,0.006812657,0.003227713,0.002173224,0.003473756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006880039,"about_ca_system_score_gemma":0.0003043503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008023435,"about_ca_topic_score_gemma":0.0003282962,"domain_scores_codex":[0.9949871,0.001142872,0.0004552796,0.001443577,0.001554392,0.0004167772],"domain_scores_gemma":[0.9955493,0.001709871,0.0005372385,0.0007871826,0.001075341,0.0003410343],"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":[0.0002328479,0.00009277414,0.003931509,0.0004689288,0.00005194305,0.0004757804,0.001351117,0.01226608,0.0479256,0.7827641,0.009832621,0.1406066],"study_design_scores_gemma":[0.00005970045,0.0005560957,0.009973999,0.0004965404,0.0000990748,0.004592097,0.0009996968,0.09923537,0.04915127,0.5769264,0.257624,0.0002856936],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03533422,0.0035695,0.883352,0.0007967347,0.0003627107,0.0002030445,0.0008876634,0.001521274,0.07397273],"genre_scores_gemma":[0.5793136,0.002164342,0.3953082,0.0008421429,0.0007474454,0.0007839625,0.001112228,0.000997512,0.01873054],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008225363,"threshold_uncertainty_score":0.02751654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007197597933067203,"score_gpt":0.2407360184229481,"score_spread":0.2335384204898809,"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."}}