{"id":"W3203865008","doi":"10.18280/ts.380435","title":"Image Recognition of Modern Agricultural Fruit Maturity Based on Internet of Things","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Office for Philosophy and Social Sciences","keywords":"Maturity (psychological); Internet of Things; Pyramid (geometry); Computer science; Context (archaeology); Artificial intelligence; Computer vision; Judgement; Image (mathematics); The Internet; Agriculture; Pattern recognition (psychology); Mathematics; Computer security; World Wide Web; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001418666,0.0001394443,0.0002111707,0.000009806982,0.00004179677,0.00002851768,0.0001440679,0.00007682172,0.001971064],"category_scores_gemma":[0.00001809141,0.00004868394,0.0001737505,0.0002095249,0.00003887993,0.0001485445,0.00003364588,0.0001062774,0.00001670032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001591787,"about_ca_system_score_gemma":0.000007053342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006227318,"about_ca_topic_score_gemma":0.00004947786,"domain_scores_codex":[0.9989172,0.00007696696,0.0002952651,0.0002321551,0.0003138329,0.0001645498],"domain_scores_gemma":[0.9994398,0.0001138327,0.0001493489,0.00003748611,0.0002035571,0.00005593021],"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":[0.00006403474,0.0004172939,0.0008155371,0.00002804038,0.00002230728,0.000005958404,0.0002127192,0.000006941875,0.9682166,0.00005584876,0.002398032,0.02775666],"study_design_scores_gemma":[0.0005274778,0.0006493457,0.2315526,0.0001970788,0.0000534745,0.000007286577,0.0003805532,0.001197928,0.763136,0.0008310256,0.001195388,0.0002719459],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958263,0.00004605955,0.00006474388,0.0008283002,0.00006412155,0.0001404019,0.0000750469,0.00003041013,0.002924582],"genre_scores_gemma":[0.9983417,0.000005327722,0.0005172497,0.0004087532,0.0001413096,0.00000690873,0.0004593213,7.472318e-7,0.0001186589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.230737,"threshold_uncertainty_score":0.9989412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01989931168559374,"score_gpt":0.2029466607325227,"score_spread":0.183047349046929,"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."}}