{"id":"W2142324784","doi":"10.1109/crv.2008.37","title":"A New Miniaturized Embedded Stereo-Vision System (MESVS-I)","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Stereopsis; Image processing; Machine vision; Image (mathematics)","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":[0.00031139,0.000443187,0.0004423964,0.0004113817,0.000133906,0.0004713422,0.001116936,0.0004068183,0.005832964],"category_scores_gemma":[0.000386511,0.000319297,0.0003039044,0.0003284101,0.0001766951,0.0008302791,0.0006680714,0.0005034181,0.001549681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003222847,"about_ca_system_score_gemma":0.0004284953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005462843,"about_ca_topic_score_gemma":0.0009285657,"domain_scores_codex":[0.9996359,0.00002749866,0.00001488981,0.0000836879,0.000203593,0.00003438087],"domain_scores_gemma":[0.9998299,0.00002254332,0.00002124941,0.00003311129,0.00006594368,0.0000272737],"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":[0.0002069057,0.00007543058,0.001425809,0.0003301369,0.00004925139,0.0001962356,0.00009641685,0.004882938,0.6950703,0.003517167,0.006008032,0.2881414],"study_design_scores_gemma":[0.0003921819,0.002526888,0.0205155,0.0001123083,0.0002370108,0.003272599,0.0001296133,0.1430304,0.6592025,0.002411595,0.1679711,0.0001983193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1256755,0.001061638,0.8495008,0.0002672673,0.0003075873,0.0003962614,0.00105129,0.008655313,0.01308432],"genre_scores_gemma":[0.315284,0.0003331849,0.6717802,0.0003186709,0.00008854162,0.0002326102,0.001347498,0.0002796198,0.0103357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005832964,"threshold_uncertainty_score":0.01951325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01431755004243166,"score_gpt":0.2628358091906314,"score_spread":0.2485182591481997,"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."}}