{"id":"W4255468726","doi":"10.1515/iupac.78.0298","title":"Food Chain—Primary Consumers","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Relation (database); Computer science; Pesticide; Chemical nomenclature; Data science; Management science; Ecology; Engineering; Biology; Chemistry; Data mining","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":[0.0005949237,0.001275764,0.001019496,0.003820106,0.0006301518,0.001787381,0.001714897,0.001168019,0.1132759],"category_scores_gemma":[0.005315538,0.0004467453,0.000848151,0.009848405,0.0002926181,0.001763821,0.001383666,0.001247768,0.08518152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001513839,"about_ca_system_score_gemma":0.002139001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04492959,"about_ca_topic_score_gemma":0.06295241,"domain_scores_codex":[0.9991622,0.00009232377,0.0001636379,0.0002844285,0.0001947517,0.0001026638],"domain_scores_gemma":[0.9974087,0.0005378129,0.0004434891,0.0004081029,0.001025683,0.0001762238],"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":[0.00007763701,0.00001790745,0.002916453,0.001322492,0.00003036356,0.00002567819,0.00004420229,0.0001602912,0.00008835649,0.0006265347,0.9900897,0.004600299],"study_design_scores_gemma":[0.00009121879,0.00001523181,0.01237316,0.0008023354,0.00002455397,0.00005507263,0.0001743288,0.0001503879,0.0001437495,0.0009359726,0.9852106,0.0000233278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000110185,0.00004745591,0.00002237609,0.00003030128,0.000008730921,0.000009331888,0.999064,0.00003222953,0.000675396],"genre_scores_gemma":[0.0004915445,0.0001000462,0.0001415516,0.00005201054,0.000005414353,0.00008247399,0.997848,0.00001772789,0.001261136],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1132759,"threshold_uncertainty_score":0.3789457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607055471777247,"score_gpt":0.3261838589646388,"score_spread":0.3101133042468663,"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."}}