{"id":"W2975103748","doi":"10.18280/ria.330208","title":"Apple Binocular Visual Identification and Positioning System","year":2019,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Computer vision; Artificial intelligence; Computer science; Preprocessor; Binocular vision; Binocular disparity; Identification (biology); Stereopsis; Subtraction; Machine vision; Positioning system; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004674579,0.0006684064,0.0007676292,0.001665174,0.0005132386,0.0007171633,0.000743378,0.0005948169,0.01616592],"category_scores_gemma":[0.0006749848,0.0002893556,0.0003019748,0.000986918,0.000218752,0.0006334342,0.0009626165,0.0004072993,0.004456701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005582434,"about_ca_system_score_gemma":0.001002535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003299457,"about_ca_topic_score_gemma":0.003456806,"domain_scores_codex":[0.998861,0.0000848124,0.00005469194,0.0002839853,0.0006253552,0.00009026735],"domain_scores_gemma":[0.9993281,0.00004557115,0.00004563608,0.00007021354,0.0004558274,0.0000546319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006772468,0.0001326322,0.006997646,0.0009798659,0.00005189228,0.0004732203,0.000434057,0.003216428,0.3847535,0.009329741,0.0484931,0.5444607],"study_design_scores_gemma":[0.0003350877,0.001802626,0.06573962,0.0002193212,0.0003368415,0.006945499,0.0004990292,0.1188429,0.3738871,0.004102288,0.4266993,0.0005902626],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0576195,0.001329452,0.8499605,0.0002363605,0.0005501008,0.0009923429,0.003530591,0.02487683,0.06090432],"genre_scores_gemma":[0.4605174,0.0009079503,0.460283,0.0005183672,0.000169152,0.001082548,0.006534503,0.0006498511,0.06933715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01616592,"threshold_uncertainty_score":0.05408037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362872090169649,"score_gpt":0.2250691910193072,"score_spread":0.2114404701176107,"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."}}