{"id":"W2069856729","doi":"10.1007/bf03263267","title":"Species Status and Relationship Between Roccella montagnei and Roccella belangeriana Using DNA Sequence Data of Nuclear Ribosomal Internal Transcribed Spacer Region","year":2008,"lang":"en","type":"article","venue":"Journal of Plant Biochemistry and Biotechnology","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Council of Scientific and Industrial Research, India; Multiple Sclerosis Scientific Research Foundation","keywords":"Biology; Ribosomal DNA; Internal transcribed spacer; Phylogenetic tree; Nuclear DNA; Ribosomal RNA; DNA sequencing; Botany; Maximum parsimony; Evolutionary biology; DNA; Phylogenetics; Genetics; Mitochondrial DNA; Clade; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001370199,0.0001260827,0.0002058161,0.00009093417,0.0001166576,0.00001917219,0.0001978807,0.0003461038,0.000004527519],"category_scores_gemma":[0.0001259502,0.0001166821,0.0000319597,0.00007681391,0.0004616932,0.00001604746,0.0001158134,0.0002069317,2.027149e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000104654,"about_ca_system_score_gemma":0.00005347063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001984875,"about_ca_topic_score_gemma":0.000006313116,"domain_scores_codex":[0.9990791,0.00003241442,0.0003832484,0.0002640112,0.0001005272,0.0001406898],"domain_scores_gemma":[0.9991477,0.00002946193,0.0003861093,0.0002810461,0.00007188258,0.00008376968],"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":[0.0001097554,0.00002393593,0.0390824,0.00005886859,0.00005373666,0.00001367922,0.00008030859,6.112475e-7,0.9598389,0.00009975612,0.0004606047,0.0001774838],"study_design_scores_gemma":[0.0006529764,0.000190386,0.02590992,0.00007155896,0.00008015256,0.00236637,0.0005080724,0.00007349067,0.9612215,0.00003141572,0.008713605,0.0001805942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970365,0.001487539,0.0004783118,0.0006203887,0.00005074502,0.00005287776,0.0002376048,0.000006442628,0.00002959227],"genre_scores_gemma":[0.9957759,0.002844164,0.0009770065,0.00001865395,0.0000980338,2.752905e-7,0.0001416939,0.000009269077,0.0001349473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01317248,"threshold_uncertainty_score":0.4758157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1076736190830758,"score_gpt":0.2824994655730514,"score_spread":0.1748258464899756,"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."}}