{"id":"W4394113122","doi":"10.6084/m9.figshare.21103774.v1","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; Environmental science; Business; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007330983,0.00145275,0.0008009914,0.002211575,0.0004462539,0.0009020177,0.0013152,0.001224893,0.0182511],"category_scores_gemma":[0.002667201,0.00027494,0.0008499884,0.003280935,0.0002599261,0.0005133186,0.00097461,0.0007405921,0.02400715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008318473,"about_ca_system_score_gemma":0.001142669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02663779,"about_ca_topic_score_gemma":0.03828939,"domain_scores_codex":[0.9993678,0.00006884357,0.00007737309,0.0002282948,0.0001671995,0.00009067129],"domain_scores_gemma":[0.9988593,0.0002260138,0.0001824596,0.0002684686,0.0003681623,0.00009560658],"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":[0.0007331192,0.0002236131,0.03447759,0.002143654,0.000228854,0.0002698967,0.0001044362,0.002369495,0.002976897,0.0008378159,0.9311029,0.02453156],"study_design_scores_gemma":[0.0003117374,0.0001360437,0.1074178,0.0005617281,0.0001759663,0.0003357951,0.0002805358,0.002377475,0.003046073,0.001411021,0.8838562,0.00008960024],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001515371,0.00005344154,0.0000902587,0.00002267253,0.00001034767,0.0000118548,0.9978351,0.0001193864,0.0003416118],"genre_scores_gemma":[0.001931936,0.00003843918,0.0003350144,0.00002045338,0.000003283154,0.00005110311,0.9971175,0.0000176476,0.0004846372],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02663779,"threshold_uncertainty_score":0.06105596,"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."}}