{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0330709,0.0003382926,0.0004187777,0.001630296,0.007213403,0.01347614,0.002069605,0.008256497,0.02132203],"category_scores_gemma":[0.1711857,0.0002297388,0.0007028372,0.002285919,0.006414254,0.009299493,0.007289163,0.008264189,0.001968185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009129058,"about_ca_system_score_gemma":0.008737889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004107329,"about_ca_topic_score_gemma":0.00703214,"domain_scores_codex":[0.9073018,0.07389824,0.001847976,0.002175506,0.01109607,0.003680259],"domain_scores_gemma":[0.7856548,0.1681003,0.01007168,0.003231915,0.0231775,0.009763794],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003801665,0.0001429509,0.003545575,0.001961063,0.0001450508,0.001271824,0.03003801,0.0007972711,0.0007754695,0.2683035,0.5711945,0.1214445],"study_design_scores_gemma":[0.00005079288,0.0001153174,0.005244587,0.002698822,0.00006940968,0.0001888236,0.0346134,0.0004230474,0.0004351248,0.0503498,0.9057083,0.0001026049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01354566,0.005834715,0.0007249169,0.8972705,0.01556259,0.00003457214,0.0001257379,0.0000244142,0.0668769],"genre_scores_gemma":[0.7187119,0.01340423,0.001657037,0.1947073,0.04366442,0.0002437028,0.0001515707,0.0001750095,0.02728485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9669291,"threshold_uncertainty_score":0.1748978,"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."}}