{"id":"W2036910230","doi":"10.1007/s10681-014-1144-y","title":"IMP-HRM: an automated pipeline for high throughput SNP marker resource development for molecular breeding in orphan crops","year":2014,"lang":"en","type":"article","venue":"Euphytica","topic":"Agricultural pest management studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Saskatchewan Pulse Growers","keywords":"Biology; Indel; Molecular breeding; Genetics; Intron; Biotechnology; Single-nucleotide polymorphism; Molecular marker; Genome; Computational biology; Gene; Genotype","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.004187011,0.002923968,0.002191782,0.003752888,0.001358372,0.002413224,0.003102474,0.001490793,0.02769555],"category_scores_gemma":[0.01015199,0.002059887,0.002534538,0.002554778,0.0005499133,0.001860913,0.00220433,0.002582167,0.01457617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009090517,"about_ca_system_score_gemma":0.002516439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006103668,"about_ca_topic_score_gemma":0.01079653,"domain_scores_codex":[0.9984111,0.0002857843,0.0001260584,0.0006973023,0.0003321859,0.0001475938],"domain_scores_gemma":[0.9965665,0.002014653,0.000371721,0.0004830752,0.0003997324,0.0001642086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002713234,0.0004517607,0.01664757,0.003213521,0.00162219,0.001089071,0.001337635,0.01355034,0.1030169,0.006649527,0.3133743,0.5363339],"study_design_scores_gemma":[0.001881459,0.0007288131,0.04574212,0.0004612235,0.001070149,0.001709354,0.0006128993,0.413963,0.2141915,0.03596002,0.2827653,0.0009141369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0119503,0.0007353557,0.5916159,0.0002762395,0.0002028374,0.0005361261,0.05394142,0.3375664,0.003175376],"genre_scores_gemma":[0.04821401,0.0003320177,0.8685387,0.0006533487,0.00008944576,0.001479914,0.05702187,0.01861367,0.005057073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02769555,"threshold_uncertainty_score":0.09265077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02439832952022394,"score_gpt":0.2585245305574447,"score_spread":0.2341262010372208,"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."}}