{"id":"W4410609787","doi":"10.1002/ael2.70018","title":"The value and broader impacts of agricultural and environmental scientific meetings","year":2025,"lang":"en","type":"article","venue":"Agricultural & Environmental Letters","topic":"Conferences and Exhibitions Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Value (mathematics); Agriculture; Environmental science; Environmental resource management; Environmental planning; Geography; Mathematics; Statistics; Archaeology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002672481,0.0001454875,0.0001225471,0.00003343444,0.001395723,0.0002667485,0.0001765411,0.00004330989,0.00003441908],"category_scores_gemma":[0.00001272803,0.00008237804,0.00006270412,0.0001250478,0.001365587,0.0002439169,0.0002092448,0.00009444818,0.000007232497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223403,"about_ca_system_score_gemma":0.000006271708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005381318,"about_ca_topic_score_gemma":0.0002548744,"domain_scores_codex":[0.9987891,0.00009819632,0.000200334,0.0002878184,0.000316203,0.0003083125],"domain_scores_gemma":[0.9996182,0.00009330608,0.00009209438,0.000106717,0.000002984021,0.00008663999],"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":[0.00002642385,0.0001990462,0.0839083,0.00004517815,0.0002400094,0.00000341672,0.01566572,0.00005204729,0.8315162,0.02113087,0.02734541,0.01986736],"study_design_scores_gemma":[0.0002232698,0.0000218846,0.943231,0.00003166275,0.00005354797,0.000002340287,0.03291215,0.000003624036,0.001567241,0.00008237458,0.02171585,0.0001550951],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844877,0.0007266238,0.000002663874,0.01262072,0.0001767484,0.0003156887,0.00001706317,0.0000155311,0.001637323],"genre_scores_gemma":[0.9971288,0.000659013,0.00004222939,0.0003556689,0.00004334758,0.00001443491,0.00003263275,0.000002791278,0.001721115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8593227,"threshold_uncertainty_score":0.9999043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003896416915535994,"score_gpt":0.2008868787824481,"score_spread":0.1969904618669121,"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."}}