{"id":"W2536567159","doi":"10.1111/1751-7915.12449","title":"The plant microbiome in biotechnology","year":2016,"lang":"en","type":"article","venue":"Microbial Biotechnology","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microbiome; Metagenomics; Biology; Biotechnology; Plant biology; Computational biology; Data science; Genetics; Computer science; Botany","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":[],"consensus_categories":[],"category_scores_codex":[0.0001388097,0.0001628613,0.0001390929,0.0001175474,0.0001387872,0.00001409892,0.0004270907,0.0008727852,0.00000815055],"category_scores_gemma":[0.00007521653,0.00008826057,0.00005269938,0.0001719761,0.0004512933,0.000002923354,0.000180412,0.0001327236,0.00009235336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003704453,"about_ca_system_score_gemma":0.00006429236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007892503,"about_ca_topic_score_gemma":0.005380825,"domain_scores_codex":[0.9989147,0.00004228963,0.0002296787,0.0003861177,0.000036024,0.0003911812],"domain_scores_gemma":[0.9994501,0.00001546539,0.00006977582,0.0004191577,0.00002040055,0.00002507369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005251032,0.00002298185,0.00008491514,0.000001881985,0.00001850112,0.0000104076,0.000005728171,4.109535e-7,0.9682956,0.001697225,0.01592635,0.01388343],"study_design_scores_gemma":[0.0002897994,0.00007110816,0.00003979453,0.000008028014,0.000002245738,0.0001387228,0.000008403857,4.344999e-7,0.5491862,0.00003618036,0.450129,0.0000900814],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515668,0.002988641,0.001087462,0.0432889,0.000485338,0.0002663608,0.0001101384,0.00009232889,0.0001139902],"genre_scores_gemma":[0.9930359,0.003456815,0.0002993068,0.0002932191,0.0001767668,0.00002419314,0.0001063484,0.00002163847,0.002585881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4342027,"threshold_uncertainty_score":0.6731719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006565809127981934,"score_gpt":0.1976562936262262,"score_spread":0.1910904844982442,"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."}}