{"id":"W2945712785","doi":"10.3390/plants8050128","title":"Mutation Breeding in Tomato: Advances, Applicability and Challenges","year":2019,"lang":"en","type":"review","venue":"Plants","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Mutagenesis; Genome editing; Genome; Biology; Computational biology; Biotechnology; Insertional mutagenesis; Molecular breeding; Mutation breeding; Mutation; Identification (biology); Whole genome sequencing; Trait; Forward genetics; Genetics; Computer science; Mutant; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001055213,0.0001545891,0.0003671663,0.0000385818,0.00000955793,0.000007215966,0.00007665496,0.0001803844,0.000001714287],"category_scores_gemma":[0.00001904769,0.0001426424,0.00004610105,0.00002545937,0.00001126375,0.000001583974,0.0000566984,0.00008039226,0.000006760336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009315155,"about_ca_system_score_gemma":0.0000206541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002672918,"about_ca_topic_score_gemma":0.00002550483,"domain_scores_codex":[0.9993141,0.00001923266,0.0001728113,0.0003110841,0.00005013862,0.0001325778],"domain_scores_gemma":[0.9997243,0.00002219124,0.00004934156,0.0001674147,0.000006067963,0.00003069375],"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":[0.000002234119,0.00000766337,0.0000141695,0.008632399,0.00001335148,0.000002129152,0.00001354927,0.000008771922,0.00005433693,0.000005262178,0.00001071276,0.9912354],"study_design_scores_gemma":[0.0001129258,0.0000362347,0.00007366679,0.001136758,0.00002673273,0.00006443249,0.00001913163,0.0000199533,0.00009634601,0.000008803226,0.9982213,0.0001837157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006996569,0.9984588,0.00009071027,0.000003800642,0.00009378237,0.0002748432,0.00003105884,0.000006767368,0.0003405561],"genre_scores_gemma":[0.001080316,0.9985012,0.0001118714,0.000003213333,0.00008305802,0.00003951009,0.0001429533,0.00001673958,0.0000211091],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9982106,"threshold_uncertainty_score":0.581679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433873332759436,"score_gpt":0.3605978910574847,"score_spread":0.3172105577815412,"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."}}