{"id":"W2898222722","doi":"10.1038/s41598-018-34431-6","title":"Artificially designed hybrids facilitate efficient generation of high-resolution linkage maps","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Japan Society for the Promotion of Science","keywords":"Linkage (software); Hybrid; Computer science; High resolution; Computational biology; Biology; Genetics; Geography; Gene; Remote sensing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007720632,0.0005691382,0.0005136103,0.0008072578,0.0003829594,0.0007697623,0.0006631163,0.000842174,0.002208452],"category_scores_gemma":[0.001107067,0.0004928873,0.0005608776,0.0005577854,0.0004900871,0.0006739955,0.001189169,0.001396064,0.001182724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003277358,"about_ca_system_score_gemma":0.0002407377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001704115,"about_ca_topic_score_gemma":0.0005389048,"domain_scores_codex":[0.9995035,0.0001091974,0.00005397174,0.0001358903,0.0001459805,0.00005152072],"domain_scores_gemma":[0.9992365,0.0003222229,0.0001580481,0.0001312958,0.00009704059,0.0000548204],"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":[0.00008401594,0.00004750053,0.000383063,0.0001705097,0.00002830598,0.0002039197,0.00009448815,0.001458208,0.9824241,0.003152909,0.0002657153,0.01168717],"study_design_scores_gemma":[0.00003860076,0.0001556869,0.001599374,0.00002273986,0.00007084737,0.0004084396,0.00005138129,0.008472523,0.9591815,0.00120535,0.02874395,0.00004951673],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3122746,0.001814105,0.6709232,0.0003213797,0.0003349159,0.0004649101,0.001836487,0.003504127,0.008526414],"genre_scores_gemma":[0.5500565,0.001384893,0.4322193,0.0002274678,0.00006105093,0.0008931843,0.005625552,0.0007892659,0.008742849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002208452,"threshold_uncertainty_score":0.007387996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03769751061061514,"score_gpt":0.2317407353762241,"score_spread":0.194043224765609,"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."}}