{"id":"W6926383143","doi":"10.25384/sage.23804714.v1","title":"sj-xlsx-3-hol-10.1177_09596836231185827 – Supplemental material for Multi-proxy reconstruction of climate changes in the Lower St. Lawrence Estuary, Canada, during the Middle and Late-Holocene","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Holocene; Climate system; Climate state; Global warming","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0008606534,0.001879959,0.001671247,0.003588638,0.001709043,0.003645854,0.003438177,0.001939446,0.2259878],"category_scores_gemma":[0.00464659,0.001180108,0.001206375,0.01030182,0.0005081982,0.001328117,0.002246543,0.001998633,0.1525236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005507947,"about_ca_system_score_gemma":0.01142885,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6139427,"about_ca_topic_score_gemma":0.7851141,"domain_scores_codex":[0.9992114,0.00006012418,0.0000713388,0.0002140398,0.0002130778,0.0002299333],"domain_scores_gemma":[0.9968424,0.0007107009,0.0002572426,0.0004603414,0.001328819,0.0004004945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000304043,0.0000109167,0.001480951,0.0005139619,0.00003771468,0.00001481855,0.00004161117,0.0002417565,0.00006871385,0.0003455309,0.9958431,0.001370361],"study_design_scores_gemma":[0.0002495769,0.000007443419,0.01304559,0.0003818588,0.00004764721,0.00002509216,0.0001413512,0.0002326004,0.0002197295,0.000635013,0.9849712,0.00004276269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003131796,0.00001745158,0.00001593262,0.00001407754,0.000004993942,0.000002261865,0.9995406,0.00007944626,0.0002939578],"genre_scores_gemma":[0.0003579989,0.00004360283,0.0001715455,0.00002736805,0.000003848279,0.00003078323,0.9981114,0.0001089021,0.001144643],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3860573,"threshold_uncertainty_score":0.7766618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0417293078887356,"score_gpt":0.2601019503908816,"score_spread":0.218372642502146,"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."}}