{"id":"W6948333298","doi":"10.5064/f6buax58/c0lhvx","title":"Burke_EDI_NENA.inventory.text.2017.10.08.tab","year":2018,"lang":"en","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"Plant chemical constituents analysis","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Data source; Workbook; Listing (finance); Data file; Web page; File format; Information source (mathematics); Microsoft Office","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008614591,0.0005833682,0.0007694978,0.0001048006,0.0007942442,0.0001682078,0.003963721,0.0005958058,0.002285519],"category_scores_gemma":[0.0005727545,0.0003017347,0.0002821512,0.0006326615,0.0008823983,0.0007648763,0.002110673,0.0006407396,0.001255356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003022067,"about_ca_system_score_gemma":0.0001178612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005380813,"about_ca_topic_score_gemma":0.002300859,"domain_scores_codex":[0.9952775,0.001172707,0.0005076994,0.001592773,0.0008589973,0.0005902719],"domain_scores_gemma":[0.9962125,0.001156322,0.0007479681,0.001056668,0.0004047794,0.0004217151],"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":[0.0001252131,0.0001913095,0.00001195475,0.00004341363,0.000407993,0.0003731285,0.0001441176,1.07987e-7,0.004810544,0.00001487897,0.9937986,0.00007878936],"study_design_scores_gemma":[0.0002114799,0.00007800464,0.00004148321,0.0001270561,0.0005383391,0.00002234323,0.002288694,0.00001053513,0.0001457231,0.00001467661,0.9958115,0.0007101967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006060992,0.0001606284,0.000002114696,0.0002035469,0.0006483954,0.000240136,0.991375,0.0001066732,0.00120251],"genre_scores_gemma":[0.0003277026,0.0001962993,0.00007399706,0.00009732314,0.001492172,0.000001306302,0.9927379,0.000002559522,0.005070779],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005733289,"threshold_uncertainty_score":0.9999435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06899340585072107,"score_gpt":0.2956721129426986,"score_spread":0.2266787070919775,"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."}}