{"id":"W1511985402","doi":"10.1109/icip.2003.1246983","title":"Multibaseline stereo using a single-lens camera","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Stereo camera; Baseline (sea); Computer science; Stereopsis; Artificial intelligence; Computer vision; Stereo cameras; Computer stereo vision; Process (computing); Lens (geology); Optics; Geology","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":[0.0004194821,0.0007425249,0.0007449481,0.0007649842,0.0004832648,0.0009983387,0.0009533386,0.001059892,0.006234236],"category_scores_gemma":[0.0009240579,0.000648224,0.0007657347,0.001015447,0.0003183629,0.00206508,0.001658638,0.001173778,0.003053142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005344208,"about_ca_system_score_gemma":0.000643207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164102,"about_ca_topic_score_gemma":0.003987878,"domain_scores_codex":[0.9990081,0.0001004517,0.00003425769,0.0002941046,0.0005015159,0.00006156553],"domain_scores_gemma":[0.9996203,0.00005463984,0.00005426849,0.0001308823,0.0001071706,0.00003282106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002873044,0.0001311103,0.001439334,0.0005505413,0.0001112739,0.0004370545,0.0002437068,0.01934939,0.3474741,0.03378684,0.009081678,0.5871077],"study_design_scores_gemma":[0.0001060801,0.0007797104,0.01005039,0.0001801176,0.0001536128,0.006582452,0.000180153,0.5433423,0.3053616,0.02553762,0.1074916,0.000234449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006999918,0.0004117681,0.9853649,0.0001090495,0.00007581022,0.00005641786,0.0001874582,0.0009056839,0.005889024],"genre_scores_gemma":[0.07231323,0.0005032237,0.9235426,0.00008082027,0.00007424567,0.00003876483,0.0002261515,0.00007480315,0.003146319],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006234236,"threshold_uncertainty_score":0.02085555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05373167655826354,"score_gpt":0.3009396021575415,"score_spread":0.247207925599278,"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."}}