{"id":"W3111535311","doi":"10.1364/oe.417575","title":"Focus issue introduction: 3D image acquisition and display: technology, perception, and applications","year":2020,"lang":"en","type":"article","venue":"Optics Express","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Focus (optics); Computer science; Scope (computer science); Conjunction (astronomy); Feature (linguistics); Perception; Imaging science; Image processing; Computer graphics (images); Artificial intelligence; Optics; Image (mathematics); Physics; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002215463,0.0001254508,0.0001233732,0.00006189243,0.00008000242,0.00005465735,0.0001088508,0.0001042288,0.0000178407],"category_scores_gemma":[0.00004362346,0.0001337252,0.00001000345,0.0001975447,0.000292274,0.000222766,0.0001316963,0.0002010126,0.00003113567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001947562,"about_ca_system_score_gemma":0.00000188559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.157133e-7,"about_ca_topic_score_gemma":1.392229e-7,"domain_scores_codex":[0.9994143,0.000003648142,0.0001227998,0.0002449194,0.00005998745,0.0001543626],"domain_scores_gemma":[0.9996324,0.00001838705,0.00001715071,0.0002272841,0.00004536278,0.00005944502],"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":[0.0000168264,0.00004709242,0.0003254729,0.0003667176,0.00006117205,0.00001239145,0.000539016,0.004244774,0.7871573,0.0492851,0.006221594,0.1517226],"study_design_scores_gemma":[0.001891686,0.0003347042,0.001238834,0.0001079382,0.0002491488,0.0002676901,0.004934577,0.4600096,0.1560329,0.06685317,0.3058809,0.002198883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02187332,0.0009989411,0.9561678,0.01735705,0.00006475965,0.0003480702,0.0000247398,0.002281808,0.0008834993],"genre_scores_gemma":[0.4919715,0.0008608502,0.5062888,0.00007788491,0.0005325327,0.0001711055,0.00001468607,0.00004540884,0.00003728761],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6311244,"threshold_uncertainty_score":0.5453154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005233474609423138,"score_gpt":0.2252459967771803,"score_spread":0.2200125221677571,"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."}}