{"id":"W4395237052","doi":"10.15468/4t4bm5","title":"Nordic crop wild relative priority list","year":2023,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Sustainable Agricultural Systems Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nordic Life Science Pipeline (Canada)","funders":"","keywords":"Crop; Geography; Environmental science; Forestry","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":[0.001142816,0.001204026,0.001203026,0.006896016,0.001259956,0.002537987,0.001374967,0.001187958,0.03000258],"category_scores_gemma":[0.005486669,0.000443049,0.0007688082,0.007293713,0.0003519716,0.00145444,0.001581288,0.00155677,0.02397529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00185961,"about_ca_system_score_gemma":0.003547835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03335448,"about_ca_topic_score_gemma":0.04453828,"domain_scores_codex":[0.9986175,0.0001554704,0.0001817214,0.0004696856,0.0003794318,0.0001962674],"domain_scores_gemma":[0.9971999,0.0006522032,0.0003695258,0.0003649278,0.001170641,0.0002427656],"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":[0.0003730526,0.00009477502,0.03133423,0.002753934,0.0001064497,0.0003735615,0.0004531906,0.002513663,0.002121326,0.006345558,0.903836,0.04969424],"study_design_scores_gemma":[0.00006632785,0.00002629094,0.02032114,0.000805333,0.00002931403,0.0001570181,0.0005625141,0.0007410222,0.00060483,0.00156732,0.9750773,0.00004163579],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004361802,0.0005743994,0.0007451713,0.0001260085,0.0001090318,0.00006368815,0.9874851,0.0003388957,0.006195839],"genre_scores_gemma":[0.005024059,0.0003178246,0.003158347,0.00007660209,0.0000165894,0.0001675114,0.9890197,0.0001236722,0.002095711],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03335448,"threshold_uncertainty_score":0.1003686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204493214187531,"score_gpt":0.2824473915991801,"score_spread":0.261998070180427,"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."}}