{"id":"W6929535997","doi":"10.5061/dryad.6g206","title":"Data from: Tracking the history and ecological changes of rising double-crested cormorant populations using pond sediments from islands in eastern Lake Ontario","year":2015,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Japanese History and Culture","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Environment and Climate Change Canada; Queen's University","funders":"","keywords":"Cormorant; Population; Vegetation (pathology); Biomass (ecology); Sediment; Habitat; Competition (biology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001244042,0.0002194837,0.000149515,0.0008814226,0.0008818397,0.0005930722,0.0002843091,0.0001636759,0.001050939],"category_scores_gemma":[0.0004707618,0.0001381103,0.000124461,0.00148775,0.0003556337,0.0001723778,0.0004839621,0.0001201555,0.0002365714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003066603,"about_ca_system_score_gemma":0.00232715,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8276746,"about_ca_topic_score_gemma":0.9701551,"domain_scores_codex":[0.9998481,0.000006822139,0.000009001566,0.00004174375,0.00005866977,0.00003553818],"domain_scores_gemma":[0.9993463,0.00002599477,0.0001402934,0.00003432547,0.0003408856,0.0001121875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000649554,0.00001906806,0.9811586,0.00005273791,0.00003629902,0.0001565922,0.001626092,0.0001204454,0.006104976,0.00002503015,0.0008917814,0.009743408],"study_design_scores_gemma":[0.000001580215,0.000005447026,0.998495,0.000004018227,0.000004900437,0.00001258799,0.0003271198,0.0000728633,0.0002063936,0.00000339222,0.0008649683,0.000001745636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9950923,0.00009354633,0.0001275007,0.00002256278,0.000002664709,0.000024041,0.003212148,0.00002071006,0.001404652],"genre_scores_gemma":[0.9934088,0.0001432191,0.000670422,0.00002079587,0.000002935837,0.00003595308,0.003841401,0.000009588251,0.001866837],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1723254,"threshold_uncertainty_score":0.3466804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1933755612446478,"score_gpt":0.3332183921129613,"score_spread":0.1398428308683136,"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."}}