{"id":"W6920397466","doi":"10.60692/p8vqj-19v33","title":"Integrating genomics for chickpea improvement: achievements and opportunities","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Genomics; Scope (computer science); Molecular breeding; Emerging technologies; Backcrossing; Selection (genetic algorithm); Genotyping; Genomic selection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002507634,0.001003806,0.001170256,0.001659922,0.000431833,0.002758468,0.0006517793,0.001852238,0.001367446],"category_scores_gemma":[0.001062106,0.0003312385,0.0008516387,0.001854207,0.0007072995,0.002888462,0.001517967,0.00260477,0.0008181944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009188959,"about_ca_system_score_gemma":0.001548781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0014715,"about_ca_topic_score_gemma":0.002009097,"domain_scores_codex":[0.9993599,0.0001680041,0.00005882019,0.0001338627,0.0002053281,0.00007396782],"domain_scores_gemma":[0.9991441,0.0004115718,0.000105402,0.00003766113,0.0001702607,0.0001310437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001299403,0.00009339096,0.001606627,0.01424155,0.0002119824,0.0005574936,0.0004925549,0.001199615,0.05386227,0.01583046,0.0122531,0.899521],"study_design_scores_gemma":[0.00002269005,0.0004806117,0.005412588,0.004206036,0.0004163781,0.002031283,0.0004876456,0.0007902447,0.01210715,0.01272882,0.9612062,0.0001102804],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001945477,0.9878668,0.004835995,0.002676426,0.0005325957,0.00002291267,0.00005497613,0.00005798828,0.00200676],"genre_scores_gemma":[0.005319803,0.9804199,0.01193372,0.000884781,0.0003889086,0.00001352194,0.0001936163,0.00002031424,0.0008254237],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002758468,"threshold_uncertainty_score":0.01326174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07415770620768151,"score_gpt":0.1835259283104558,"score_spread":0.1093682221027743,"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."}}