{"id":"W6930345598","doi":"10.5281/zenodo.1318942","title":"KDEDOI/kactivities: KF5 release 5.48","year":2018,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Core (optical fiber); Action (physics); Component (thermodynamics); Process (computing)","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":[0.00347658,0.002735354,0.001914343,0.00380119,0.00121541,0.002474655,0.00392361,0.001430198,0.1265322],"category_scores_gemma":[0.00637512,0.001876332,0.001222129,0.002808614,0.0006320667,0.002590013,0.001708832,0.002982982,0.1773518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244793,"about_ca_system_score_gemma":0.001320023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002915476,"about_ca_topic_score_gemma":0.001801512,"domain_scores_codex":[0.9982963,0.0001976036,0.0002125524,0.0003056981,0.0007624772,0.0002254205],"domain_scores_gemma":[0.9975271,0.0005288912,0.0001885352,0.0007659702,0.0007717349,0.0002178986],"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":[0.004739821,0.0005805434,0.00324538,0.003770779,0.0002953494,0.0003214651,0.0005099198,0.003950589,0.1725338,0.03201205,0.6344585,0.1435819],"study_design_scores_gemma":[0.0003479899,0.0002226789,0.002025805,0.0001694972,0.0001408774,0.0003780513,0.00005470994,0.004103475,0.2826152,0.006669777,0.7031171,0.0001548352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.030107,0.007240545,0.287952,0.001249609,0.001309698,0.001031462,0.3772787,0.1421064,0.1517248],"genre_scores_gemma":[0.08936603,0.003313036,0.1055008,0.0004241628,0.0003044499,0.001806263,0.6658496,0.04127904,0.09215657],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1265322,"threshold_uncertainty_score":0.4232925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03074054900068796,"score_gpt":0.2148452413810045,"score_spread":0.1841046923803165,"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."}}