{"id":"W4301895198","doi":"","title":"Dynamic Programming and Skyline Extraction in Catadioptric Infrared Images","year":2009,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Catadioptric system; Skyline; Computer science; Computer vision; Artificial intelligence; Extraction (chemistry); Infrared; Feature extraction; Pattern recognition (psychology); Computer graphics (images); Data mining; Optics; Physics","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":[0.0008208064,0.0001183759,0.0001231226,0.0001792421,0.00008469281,0.0001294616,0.0001289458,0.00007454222,0.00001019157],"category_scores_gemma":[0.0001918786,0.0001335049,0.0000274433,0.0004197335,0.0000363523,0.0001801027,0.00002123511,0.0001542494,0.000004866307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006880575,"about_ca_system_score_gemma":0.00001649249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008820015,"about_ca_topic_score_gemma":0.00028269,"domain_scores_codex":[0.9989397,0.0003294726,0.0002363538,0.0001929385,0.00011788,0.0001836619],"domain_scores_gemma":[0.9991339,0.0001765215,0.00005265046,0.0003431404,0.0002256455,0.00006815294],"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":[0.00001311832,0.0003773361,0.004978022,0.0001351614,0.00002513299,0.00001746865,0.004743075,0.03278625,0.0395782,0.01333756,0.0002938556,0.9037148],"study_design_scores_gemma":[0.0006641776,9.106466e-7,0.05339633,0.000330148,0.00001461578,0.00001676856,0.0001067885,0.9177554,0.02263666,0.001255154,0.003506771,0.0003162994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3777062,0.001715739,0.6052734,0.003154682,0.00009531816,0.0003612889,0.000007699234,0.0004331665,0.01125256],"genre_scores_gemma":[0.9634879,0.00050913,0.0351539,0.00002124219,0.000005736587,0.000007364765,0.0001110185,0.00001688936,0.0006867791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9033985,"threshold_uncertainty_score":0.5444172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00534804811772829,"score_gpt":0.2085418268425837,"score_spread":0.2031937787248554,"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."}}