{"id":"W1970735862","doi":"10.1111/j.1601-5223.1948.tb02842.x","title":"LINKAGE VALUES IN AN INTERCHANGE COMPLEX IN PISUM","year":2010,"lang":"en","type":"article","venue":"Hereditas","topic":"Botanical Research and Chemistry","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"","keywords":"Linkage (software); Citation; Biology; Library science; Genetics; Genealogy; Computer science; History; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005407564,0.0002681439,0.0002754411,0.004521569,0.001303312,0.001320618,0.0005121588,0.0004458814,0.0100801],"category_scores_gemma":[0.002030921,0.0001776233,0.000202346,0.003593734,0.0005886139,0.0006628718,0.001275699,0.0006767807,0.001215846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011565,"about_ca_system_score_gemma":0.0002257123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229933,"about_ca_topic_score_gemma":0.001180188,"domain_scores_codex":[0.9994174,0.0001166868,0.00004250748,0.0001931887,0.0001840543,0.00004613022],"domain_scores_gemma":[0.9985231,0.0006253703,0.0003407558,0.0001632822,0.0001699034,0.0001776173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002736848,0.0001616024,0.1013666,0.0004729667,0.0003510686,0.002522182,0.004217083,0.0009651452,0.6954751,0.0420954,0.001783561,0.1478524],"study_design_scores_gemma":[0.0001273083,0.0006931335,0.7387853,0.00008449439,0.000334344,0.003959715,0.001703995,0.00241507,0.1637639,0.02576792,0.06224812,0.0001166997],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787304,0.001155326,0.004938469,0.0001860422,0.00004444247,0.00002233908,0.00127307,0.0001314783,0.0135184],"genre_scores_gemma":[0.9941202,0.0002533188,0.001926267,0.00002737987,0.00001856941,0.00001722067,0.001639253,0.000017018,0.001980678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0100801,"threshold_uncertainty_score":0.03372127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05927145817877473,"score_gpt":0.3058479923631668,"score_spread":0.2465765341843921,"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."}}