{"id":"W2947362700","doi":"10.1002/sdtp.12843","title":"3‐4: Stereoscopic Image Quality Assessment","year":2019,"lang":"en","type":"article","venue":"SID Symposium Digest of Technical Papers","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Qualcomm (Canada); York University","funders":"Ontario Centres of Excellence","keywords":"Stereoscopy; Image quality; Computer science; Computer vision; Quality (philosophy); Artificial intelligence; Geology; Image (mathematics); Philosophy; Epistemology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008982359,0.0005001973,0.0003586771,0.00199425,0.0003083101,0.0006766882,0.0004441502,0.0006860877,0.009746261],"category_scores_gemma":[0.001864845,0.000145684,0.000520304,0.0007650845,0.0003261415,0.0004295085,0.0005927444,0.0003880966,0.001161188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003132232,"about_ca_system_score_gemma":0.0002923841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002949369,"about_ca_topic_score_gemma":0.00244148,"domain_scores_codex":[0.9991409,0.00009887687,0.00006557113,0.00006135863,0.0005526065,0.00008055946],"domain_scores_gemma":[0.9984425,0.0002280302,0.0001113253,0.00009914085,0.001033958,0.00008516607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00170684,0.0002581785,0.02580841,0.0006407938,0.0001265895,0.0005687794,0.0003860979,0.005279697,0.8129697,0.0008463795,0.0023741,0.1490345],"study_design_scores_gemma":[0.0001037913,0.00253805,0.2218243,0.000102616,0.0002352946,0.003415179,0.0003515477,0.04810259,0.7146052,0.0008162116,0.007681296,0.0002240367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7947406,0.0007204166,0.1792399,0.0001474475,0.0001197272,0.00105982,0.00346474,0.001929321,0.01857808],"genre_scores_gemma":[0.921026,0.000440842,0.0653028,0.0001369626,0.00003524696,0.0003586127,0.00227371,0.0003007399,0.01012502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009746261,"threshold_uncertainty_score":0.03260446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715466027986392,"score_gpt":0.3228706819492851,"score_spread":0.3057160216694212,"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."}}