{"id":"W2911337866","doi":"10.1007/11744023_48","title":"Confocal Stereo","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer vision; Focus (optics); Computer science; Artificial intelligence; Radiance; Aperture (computer memory); Lens (geology); Pixel; Optics; Confocal; Point (geometry); Computer graphics (images); Physics; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001111155,0.0002192258,0.0001838553,0.0002075244,0.00007215786,0.0001459132,0.0005511171,0.0001641179,0.00001997175],"category_scores_gemma":[0.000004103601,0.0002125471,0.00004001767,0.0001368245,0.0002816761,0.00008972652,0.0001167543,0.0003957819,0.00002503598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001077405,"about_ca_system_score_gemma":0.00005762769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006612694,"about_ca_topic_score_gemma":0.00001055606,"domain_scores_codex":[0.9989968,0.000001656264,0.0001975216,0.0003405433,0.0002159164,0.0002475932],"domain_scores_gemma":[0.9994546,0.00004480015,0.00003600232,0.00036895,0.00005452926,0.00004109356],"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":[7.179269e-7,0.000007568164,0.000007631284,0.00007573156,0.000003778797,0.00001603712,0.00006294867,0.08149838,0.000479602,0.003597539,0.0007895888,0.9134605],"study_design_scores_gemma":[0.00009558001,0.00002813582,0.00002887963,0.0002956523,0.000007873612,0.00003313732,2.177459e-8,0.8274345,0.007340638,0.1318818,0.03225242,0.0006013385],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001676458,0.0003174272,0.9676728,0.00008424065,0.0002283981,0.0001326888,0.000005433479,0.0004122306,0.03113006],"genre_scores_gemma":[0.3435131,0.00004697159,0.6534158,0.000622233,0.0007710928,0.00002703579,0.00002267937,0.0001049446,0.001476092],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9128591,"threshold_uncertainty_score":0.866742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142197973525568,"score_gpt":0.2344636381538966,"score_spread":0.2230416584186409,"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."}}