{"id":"W7010099537","doi":"","title":"Historical Pesticide Applications in the Forests of Atlantic Canada","year":2023,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pesticide; Climate change; Agriculture; Atlantic forest; Agrochemical","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313536,0.0002874202,0.000238226,0.003205093,0.002190284,0.001452128,0.000809374,0.0003546053,0.007028269],"category_scores_gemma":[0.0009338247,0.0001656232,0.0003202888,0.006830871,0.0006712484,0.0004700495,0.0004959497,0.0005194697,0.0008196904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02740271,"about_ca_system_score_gemma":0.02247621,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9935575,"about_ca_topic_score_gemma":0.9986749,"domain_scores_codex":[0.9993145,0.0000183274,0.00002483792,0.0000890993,0.0003481625,0.0002049883],"domain_scores_gemma":[0.9985091,0.0000626063,0.0001471608,0.00003111058,0.001123742,0.0001262922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003122725,0.00009614025,0.7189752,0.001026767,0.0002668531,0.0009395209,0.003258793,0.003117003,0.003907381,0.00515358,0.06665649,0.19629],"study_design_scores_gemma":[0.000005335718,0.00002260366,0.8488464,0.0002078217,0.00007362325,0.0001826097,0.002520517,0.0006437891,0.001534634,0.0003344539,0.1455957,0.0000324834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7364197,0.02463184,0.001289469,0.003723168,0.000196963,0.00009759769,0.08597454,0.0003000538,0.1473667],"genre_scores_gemma":[0.9062154,0.01290512,0.00139912,0.0004114833,0.00004025296,0.00002158395,0.012842,0.0001116876,0.06605331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02740271,"threshold_uncertainty_score":0.1988215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01567767097952549,"score_gpt":0.2536510110610451,"score_spread":0.2379733400815196,"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."}}