{"id":"W4399546787","doi":"10.1021/acsagscitech.4c00054","title":"Environmental Impact of Outdoor Cannabis Production","year":2024,"lang":"en","type":"article","venue":"ACS Agricultural Science & Technology","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fertilizer; Environmental science; Greenhouse gas; Agriculture; Production (economics); Natural resource economics; Life-cycle assessment; Cannabis; Business; Cannabis sativa; Environmental protection; Agronomy; Ecology; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002349894,0.0001265143,0.0001840123,0.0005356468,0.0001226299,0.00003487754,0.0002491891,0.0001097026,0.0001095323],"category_scores_gemma":[0.0001259738,0.000066309,0.0001086572,0.002644374,0.00130369,0.0002241942,0.0001478527,0.0002787635,0.00004734895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005761302,"about_ca_system_score_gemma":0.0002959866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001198646,"about_ca_topic_score_gemma":0.00001025591,"domain_scores_codex":[0.9984794,0.000007156124,0.0001830394,0.000434842,0.000473186,0.0004223485],"domain_scores_gemma":[0.9994956,0.000001580831,0.00003587093,0.0002533103,0.00009653207,0.0001170844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001057308,0.00006159268,0.005182387,0.00002242828,0.00001969805,0.0000167798,0.0001133449,0.00001092951,0.9572694,0.0003447419,0.016968,0.01998007],"study_design_scores_gemma":[0.0001388227,0.0009033306,0.5719856,0.00006053508,0.00003222844,0.000891028,0.0006521595,0.00004349393,0.4151667,0.0001268605,0.009857231,0.0001420549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974601,0.0008308594,0.000002576734,0.02349794,0.0002029446,0.0003429629,0.00001071217,0.0001457999,0.0003652027],"genre_scores_gemma":[0.9924811,0.00007686752,0.0000370463,0.00001087093,0.00009474283,0.00003822015,0.000006323875,0.000006324835,0.007248511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5668032,"threshold_uncertainty_score":0.48035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007777946582454971,"score_gpt":0.2881701696863721,"score_spread":0.2803922231039171,"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."}}