{"id":"W4394247710","doi":"10.6084/m9.figshare.21103774","title":"Fresh and Aged Beef Electronic Nose Data","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electronic nose; Nose; Business; Database; Computer science; Medicine; Artificial intelligence; Anatomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001601456,0.0002506083,0.000258234,0.00001075908,0.0002749811,0.0001108517,0.00171796,0.0002177943,0.9240958],"category_scores_gemma":[0.0009738322,0.0001057707,0.00005659553,0.0002205787,0.00001405722,0.0001259224,0.00211874,0.0007783149,0.0004065093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005761217,"about_ca_system_score_gemma":0.00004284554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003160409,"about_ca_topic_score_gemma":0.01492025,"domain_scores_codex":[0.9980773,0.0001572532,0.0001931092,0.000820954,0.0003198752,0.0004314515],"domain_scores_gemma":[0.998814,0.0004573633,0.0001234756,0.0004721293,0.00002449441,0.0001085149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007962532,0.00005212803,0.000005022085,0.00006580305,0.0000147662,0.00001537105,0.000003064554,1.441749e-7,0.00003418894,1.11756e-7,0.9983517,0.001449723],"study_design_scores_gemma":[0.00005674798,0.0001898257,0.002233254,0.00006149294,0.00001441543,0.000009486597,0.0000315147,0.00000253493,0.000005183289,0.00002129737,0.9971005,0.0002737613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005009015,0.001192229,3.387062e-10,0.00027154,0.00005598931,0.0003582521,0.9975441,0.00005642411,0.00002064057],"genre_scores_gemma":[0.0004660356,0.00005728524,0.000001451586,0.0002588468,0.000282157,0.0001467876,0.9987218,0.00000138097,0.0000642595],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9236893,"threshold_uncertainty_score":0.832585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05492826540922131,"score_gpt":0.2568749240419434,"score_spread":0.2019466586327221,"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."}}