{"id":"W2055717762","doi":"10.1016/j.dsr2.2006.08.001","title":"SERIES (subarctic ecosystem response to iron enrichment study): A Canadian–Japanese contribution to our understanding of the iron–ocean–climate connection","year":2006,"lang":"en","type":"article","venue":"Deep Sea Research Part II Topical Studies in Oceanography","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Subarctic climate; Connection (principal bundle); Ecosystem; Environmental science; Climate change; Oceanography; Iron fertilization; Climatology; Series (stratigraphy); Ecology; Geology; Engineering; Biology; Phytoplankton","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0006904964,0.0004430391,0.0003296533,0.001140851,0.003263289,0.000651866,0.0006056646,0.0003421195,0.002246854],"category_scores_gemma":[0.0007128195,0.0002974016,0.0005514338,0.002100246,0.0006528999,0.0004502856,0.001089359,0.0005289572,0.0002942297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008548484,"about_ca_system_score_gemma":0.01847386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9634184,"about_ca_topic_score_gemma":0.9915086,"domain_scores_codex":[0.9997998,0.00001723401,0.00001048446,0.0000489101,0.00004312018,0.00008045622],"domain_scores_gemma":[0.9988878,0.00004145828,0.0001652285,0.00009043461,0.000337328,0.0004776742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00124098,0.0005860722,0.9417936,0.0001228267,0.0002462424,0.0008842847,0.004162852,0.0002239962,0.01027902,0.0003344572,0.007641925,0.03248369],"study_design_scores_gemma":[0.00001915224,0.00003332568,0.9963446,0.000005813491,0.00006197084,0.00005352629,0.0008836173,0.00004814415,0.0002776196,0.0000235039,0.002241166,0.000007529511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931276,0.000286527,0.00026933,0.0002497651,0.00005155246,0.0001171619,0.003441304,0.00001487015,0.00244201],"genre_scores_gemma":[0.9792498,0.0008289352,0.003302354,0.0007941084,0.00006120955,0.0002910039,0.00681829,0.00003750274,0.00861681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03658164,"threshold_uncertainty_score":0.07359409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04473940361328466,"score_gpt":0.3303571756184352,"score_spread":0.2856177720051505,"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."}}