{"id":"W6892267051","doi":"10.5061/dryad.vr300p0","title":"Data from: Genotyping-in-Thousands by sequencing (GT-seq) panel development and application to minimally-invasive DNA samples to support studies in molecular ecology","year":2019,"lang":"en","type":"dataset","venue":"DRYAD","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genotyping; DNA sequencing; Genotype; Amplicon; Molecular ecology; Population; Genomics; Multiplex; Population genomics; Population genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00128468,0.0008193252,0.001404007,0.0008993085,0.0001021435,0.00007863798,0.001737574,0.0005014931,0.00005179039],"category_scores_gemma":[0.001069977,0.0009166659,0.00003782751,0.0006560889,0.0001244462,0.000187186,0.002840675,0.0004660952,0.004346929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001814189,"about_ca_system_score_gemma":0.00123429,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001239268,"about_ca_topic_score_gemma":0.04926009,"domain_scores_codex":[0.994672,0.0002558191,0.001182306,0.002374131,0.0005599751,0.0009557588],"domain_scores_gemma":[0.996214,0.0005864333,0.00045442,0.002306321,0.0001636055,0.0002752469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001280906,0.0001033651,0.001337748,0.0003191579,0.000282323,0.0002624395,0.001363819,0.00006476244,0.04557697,0.000002234634,0.9500312,0.0005278501],"study_design_scores_gemma":[0.0009734374,0.0001844334,0.003923868,0.0003679147,0.000164783,0.00001829074,0.0009990882,0.00001598305,0.00744798,0.00003567717,0.9845917,0.001276797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1784884,0.0007953479,0.00009988301,0.00009660787,0.0001660501,0.002038868,0.8182554,0.00004635447,0.00001308795],"genre_scores_gemma":[0.004227842,0.0002997217,0.008457275,0.0010217,0.00007907989,0.0008088296,0.9849116,0.0001541479,0.00003976463],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1742606,"threshold_uncertainty_score":0.9993284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1325182609310025,"score_gpt":0.3492373874643836,"score_spread":0.2167191265333811,"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."}}