{"id":"W4415929377","doi":"10.1016/j.marmicro.2025.102526","title":"Late Holocene paleoceanography of the Knipovich Ridge area (Norwegian Sea) based on micropaleontological data","year":2025,"lang":"en","type":"article","venue":"Marine Micropaleontology","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Shirshov Institute of Oceanology, Russian Academy of Sciences; Lomonosov Moscow State University; Ministry of Science and Higher Education of the Russian Federation; Russian Science Foundation","keywords":"Paleoceanography; Ridge; Foraminifera; Holocene; Dinocyst; Holocene climatic optimum; Sea surface temperature; Diatom; Climate change","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008921996,0.0003845718,0.0006996462,0.0004317077,0.0004066132,0.00002757962,0.002617501,0.0004835126,0.001649223],"category_scores_gemma":[0.0003554281,0.0002626248,0.0002030689,0.00104455,0.00154573,0.00008087126,0.0003624971,0.0008521461,0.0001209715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002903216,"about_ca_system_score_gemma":0.0002376302,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006144082,"about_ca_topic_score_gemma":0.03145533,"domain_scores_codex":[0.9963765,0.0009228567,0.0006063113,0.0009309477,0.0002539348,0.0009094792],"domain_scores_gemma":[0.9964582,0.001024403,0.0002333112,0.002011966,0.0001406001,0.0001315363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004963006,0.0001355271,0.9924679,0.00009948711,0.00009637363,0.00007602636,0.00002140266,0.0002190795,0.00005556378,0.0001289956,0.001279287,0.00492407],"study_design_scores_gemma":[0.001115653,0.0002256129,0.9886429,0.00004167998,0.00008724078,0.00006935657,0.00002143051,0.005287822,0.0002414826,0.0005632946,0.003468185,0.0002353742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9231588,0.001107318,0.00006328124,0.006944023,0.0007280516,0.0004689627,0.0003555068,0.00006700594,0.06710704],"genre_scores_gemma":[0.996014,0.0001306959,0.000623262,0.001934276,0.00003950704,0.000004832264,0.0006376552,0.000005168336,0.0006106243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07285517,"threshold_uncertainty_score":0.9999826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.024089911901371,"score_gpt":0.2496991053112683,"score_spread":0.2256091934098973,"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."}}