{"id":"W2002462213","doi":"10.4271/2006-01-1160","title":"Perception and Autonomous Navigation Using <italic>a Priori</italic> Data","year":2006,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Perception; A priori and a posteriori; Computer science; Computer vision; Artificial intelligence; Human–computer interaction; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001037736,0.001018966,0.001032622,0.0003338629,0.000777212,0.0006087676,0.003075542,0.0009322331,0.00006535028],"category_scores_gemma":[0.0005078415,0.0009378666,0.0002992361,0.001411993,0.001186627,0.004179799,0.002472935,0.0011361,0.00006265906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005817013,"about_ca_system_score_gemma":0.0001844858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001058427,"about_ca_topic_score_gemma":0.0055038,"domain_scores_codex":[0.9932919,0.0002263676,0.001458884,0.002522574,0.001285506,0.001214738],"domain_scores_gemma":[0.9948219,0.0003545824,0.0004908313,0.003702879,0.0002372101,0.0003926083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007325046,0.0002662303,0.00009910204,0.00005139146,0.0000191594,0.00007497468,0.00002911623,0.00001212134,0.9381545,0.02973182,0.001717276,0.02977106],"study_design_scores_gemma":[0.0009093905,0.001507428,0.8633801,0.0004677533,0.0001272432,0.0007117313,0.00005205344,0.00003552983,0.001353033,0.01919295,0.1104833,0.001779493],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9151063,0.003762675,0.01344412,0.007632552,0.00100092,0.005119894,0.0004402905,0.01994788,0.03354539],"genre_scores_gemma":[0.8842888,0.0003995061,0.1133075,0.0009432843,0.0003002408,0.0001024318,0.0002424787,0.0001181796,0.0002975615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9368015,"threshold_uncertainty_score":0.9993072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297021626893459,"score_gpt":0.2908337167206098,"score_spread":0.2678635004516752,"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."}}