{"id":"W6901799042","doi":"10.60692/vb2xj-x0902","title":"Additional file 17 of Combined nature and human selections reshaped peach fruit metabolome","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Postharvest Quality and Shelf Life Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Table (database); KEGG; Metabolome; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001080913,0.001166873,0.001430351,0.002570117,0.001057984,0.001730174,0.001784434,0.001288489,0.8370286],"category_scores_gemma":[0.009824131,0.0006187063,0.001038319,0.003985733,0.0002582752,0.00153318,0.001138821,0.0008983668,0.1869089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052749,"about_ca_system_score_gemma":0.001643148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008798882,"about_ca_topic_score_gemma":0.01792923,"domain_scores_codex":[0.999432,0.00006063219,0.00008431356,0.0001844766,0.0001419277,0.00009657197],"domain_scores_gemma":[0.9926581,0.004711266,0.0004383073,0.0005717169,0.00131814,0.000302559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000505961,0.0001086042,0.00270866,0.002737779,0.00007987865,0.0001445642,0.00007929936,0.0003458818,0.0008075039,0.0004998423,0.9830595,0.008922463],"study_design_scores_gemma":[0.004397186,0.0003132687,0.05585209,0.002630694,0.0003022178,0.0007243387,0.0005296887,0.001499047,0.003531164,0.00852834,0.9214795,0.0002123756],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0001298586,0.00001069227,0.000116836,0.00003526963,0.00001372023,0.00002108081,0.9989914,0.0002502632,0.0004309462],"genre_scores_gemma":[0.003481576,0.00006361413,0.001500538,0.0002408025,0.00003868727,0.0004098776,0.9893814,0.0005194552,0.004363962],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8370286,"threshold_uncertainty_score":0.232459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02980594332820143,"score_gpt":0.2069860540794469,"score_spread":0.1771801107512455,"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."}}