{"id":"W4361265475","doi":"10.1139/cjfr-2022-0291","title":"CO<sub>2</sub> flux from <i>Acer saccharum</i> logs: sources of variation and the influence of silvicultural treatments","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flux (metallurgy); Carbon dioxide; Saccharum; Carbon cycle; Environmental science; Atmospheric sciences; Carbon fibers; Chemistry; Botany; Mathematics; Ecology; Biology; Ecosystem; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003676728,0.000353983,0.0003742117,0.0003207955,0.0002778444,0.000660445,0.0002879372,0.0002548759,0.0003751216],"category_scores_gemma":[0.0002346454,0.0001419327,0.0002923534,0.0002667644,0.000300543,0.0003139925,0.0002220553,0.0004205209,0.0001044141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000537406,"about_ca_system_score_gemma":0.0002397563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007214885,"about_ca_topic_score_gemma":0.01142611,"domain_scores_codex":[0.9997856,0.0000300877,0.00001808358,0.00008857861,0.00005108976,0.00002652515],"domain_scores_gemma":[0.9995628,0.0001120573,0.0001421607,0.00003977601,0.0000748857,0.00006833229],"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":[0.0008139072,0.0001096724,0.07305243,0.00004334122,0.00005803144,0.000081946,0.0000995211,0.0002541108,0.9215345,0.00001829593,0.00005107195,0.003883114],"study_design_scores_gemma":[0.000007106101,0.0003060091,0.9201513,0.000003408391,0.00005022862,0.0000641302,0.0001905941,0.001775603,0.07704613,0.00003148409,0.0003596245,0.0000142934],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992994,0.00006595296,0.0003181957,0.000007917989,0.000003386481,0.000006246531,0.0001589417,0.00001181644,0.0001281735],"genre_scores_gemma":[0.9987724,0.00004550409,0.0004777543,0.00003589971,0.00000351607,0.00002140242,0.000438114,0.00001485064,0.0001905382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007214885,"threshold_uncertainty_score":0.01434577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088454433954328,"score_gpt":0.2484192818862663,"score_spread":0.2175347375467231,"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."}}