{"id":"W4238101549","doi":"10.1515/iupac.81.0946","title":"Wahlund Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Ecology; Computer science; Biology; Data mining; Linguistics; Philosophy","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":[0.0009410497,0.001767104,0.001321847,0.004270395,0.0009635409,0.003455431,0.002474437,0.001872758,0.1016577],"category_scores_gemma":[0.006623502,0.0006144573,0.001364342,0.00626418,0.000421011,0.002337899,0.002276607,0.001848829,0.1585485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187093,"about_ca_system_score_gemma":0.00223578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01983846,"about_ca_topic_score_gemma":0.03922759,"domain_scores_codex":[0.9987382,0.0001887078,0.0001548101,0.0004465019,0.0003074016,0.0001644028],"domain_scores_gemma":[0.998226,0.000454058,0.0002326662,0.0004851165,0.0004328877,0.000169241],"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":[0.00009001773,0.0000225299,0.001901861,0.0006692176,0.00003404549,0.00003333659,0.00003060051,0.0002325553,0.00006336861,0.00120026,0.9871225,0.008599675],"study_design_scores_gemma":[0.00009063878,0.00001173564,0.003085093,0.0004614356,0.00001947048,0.00006531842,0.00007386457,0.0002445096,0.0001693352,0.001707666,0.9940552,0.00001584628],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002454453,0.0002395386,0.0001380933,0.0001081794,0.00004277278,0.00001560405,0.9959209,0.0003589697,0.002930432],"genre_scores_gemma":[0.0006043477,0.0001745297,0.0003659162,0.00007968877,0.00000935667,0.00006419779,0.9962628,0.00009009105,0.002348977],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1016577,"threshold_uncertainty_score":0.3400791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007807658504668299,"score_gpt":0.3506235942822425,"score_spread":0.3428159357775742,"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."}}