{"id":"W6963483783","doi":"10.21233/n3s45f","title":"Point Escuminac pollen dataset","year":2017,"lang":"en","type":"dataset","venue":"Neotoma Paleoecological Database","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pollen; Point (geometry); Raw data; Vegetation (pathology)","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","sts","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.002387744,0.002281454,0.002656505,0.0007626966,0.001438624,0.0008253356,0.008367137,0.002070065,0.03996599],"category_scores_gemma":[0.00721423,0.001883717,0.0006315003,0.0004029702,0.001767615,0.001193503,0.006312891,0.003670398,0.2360224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005936867,"about_ca_system_score_gemma":0.0006696231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008942425,"about_ca_topic_score_gemma":0.006602822,"domain_scores_codex":[0.9886877,0.001151715,0.001723937,0.003743968,0.001998692,0.002694001],"domain_scores_gemma":[0.9813801,0.001139279,0.002072418,0.01357122,0.0002424973,0.001594499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007334176,0.001523571,0.0001347205,0.0003453773,0.0002551837,0.01178704,0.000003138148,9.715585e-7,0.0000845012,0.00002525785,0.984728,0.0003788238],"study_design_scores_gemma":[0.002327163,0.0006911451,0.003564869,0.0002565732,0.0007878107,0.0004654179,0.00002211971,0.0000159237,0.00003243147,0.00007858791,0.9894381,0.002319824],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004337065,0.0004694367,0.000004924047,0.0002781319,0.001741116,0.002779141,0.9930574,0.0005460361,0.0006900811],"genre_scores_gemma":[0.00007216639,0.0005636889,0.0007554234,0.00161681,0.001522566,0.0009433305,0.9938745,0.0002137759,0.0004376788],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1960564,"threshold_uncertainty_score":0.9998614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605927199852503,"score_gpt":0.3542656623959299,"score_spread":0.3082063903974049,"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."}}