{"id":"W6889000625","doi":"10.25345/c50g3h916","title":"MassIVE MSV000095288 - GNPS_Metabolite Profiling Analysis Project","year":2024,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Profiling (computer programming); Identification (biology); Focus (optics); Troubleshooting","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":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001192494,0.001525374,0.00240308,0.005505233,0.0002284422,0.0007348702,0.00170601,0.0009038486,0.005146284],"category_scores_gemma":[0.0006669413,0.001351849,0.001725262,0.008909224,0.0002780902,0.0002891815,0.0009156547,0.002101727,0.1420647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004892761,"about_ca_system_score_gemma":0.0008376392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007557558,"about_ca_topic_score_gemma":0.001953835,"domain_scores_codex":[0.9923279,0.0006290274,0.001338082,0.002499304,0.001716517,0.00148921],"domain_scores_gemma":[0.9949331,0.0002400456,0.0008604956,0.003313539,0.0003255486,0.0003272473],"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":[0.00008382231,0.0001672404,0.0001894128,0.000780867,0.008799948,0.0007863906,0.00007259771,0.00005993869,0.0001271346,0.00005604798,0.9886767,0.0001998476],"study_design_scores_gemma":[0.0003195447,0.00006008529,0.0001166198,0.0002479702,0.0243298,0.00001438263,0.0001652245,0.0002668619,0.0003232354,0.0001480036,0.9725829,0.001425344],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002486065,0.006620867,0.000007154201,0.00002071765,0.001451588,0.001705586,0.9874455,0.000718768,0.001781249],"genre_scores_gemma":[0.00007237975,0.0002397186,0.0007902494,0.0001314803,0.001567659,0.0005712749,0.9943324,0.0004101348,0.001884652],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1369184,"threshold_uncertainty_score":0.9997495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02534045506990961,"score_gpt":0.3224113789212829,"score_spread":0.2970709238513733,"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."}}