{"id":"W4402126059","doi":"10.70099/bj/2024.09.01.33","title":"10.70099/BJ/2024.09.01.33","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"CRISPR; Orange (colour); Subgenomic mRNA; Gene; Biology; Chemistry; Computational biology; Genetics; Food science","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000509474,0.000973714,0.0006968148,0.002084992,0.001097439,0.002233624,0.001170449,0.002360569,0.9645424],"category_scores_gemma":[0.0007985119,0.0004928152,0.000763858,0.001295484,0.00068889,0.001381893,0.001840515,0.001601257,0.9669592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007105651,"about_ca_system_score_gemma":0.0007417487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002517326,"about_ca_topic_score_gemma":0.003065937,"domain_scores_codex":[0.999774,0.00001434808,0.00001431473,0.00004996446,0.00008840492,0.00005894684],"domain_scores_gemma":[0.9991062,0.0001236778,0.00003330761,0.0001342192,0.0001631236,0.0004392806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002545922,0.0002720905,0.000668999,0.000307237,0.00001941694,0.0001982593,0.0000501921,0.0002103174,0.006885328,0.004995292,0.4396307,0.5465075],"study_design_scores_gemma":[0.00003053447,0.00004774324,0.001193085,0.0001406571,0.000009096546,0.0003613811,0.0000473488,0.0001502284,0.001122457,0.001124364,0.9957584,0.00001467138],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006905936,0.000410963,0.001138109,0.0006728211,0.0004771316,0.00004743122,0.001246683,0.001431145,0.9938851],"genre_scores_gemma":[0.001334039,0.0001955039,0.0006304052,0.0002439395,0.00006470187,0.00002036042,0.0008553612,0.0003052779,0.9963504],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03545761,"threshold_uncertainty_score":0.05057591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003049609025400397,"score_gpt":0.2165828641687665,"score_spread":0.2135332551433661,"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."}}