{"id":"W6944888775","doi":"10.21233/n3km0h","title":"Lac Martyne 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":"Royal Ontario Museum","funders":"","keywords":"Pollen; Vegetation (pathology); Bee pollen; Taxonomy (biology)","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":[0.002031775,0.002091553,0.002458237,0.0006919008,0.001352436,0.0007786887,0.007733617,0.002015332,0.05154128],"category_scores_gemma":[0.005709609,0.001732697,0.0005249237,0.0003982992,0.001542325,0.0009807242,0.005756238,0.003460355,0.2657235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004163448,"about_ca_system_score_gemma":0.0005721546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008162035,"about_ca_topic_score_gemma":0.008518483,"domain_scores_codex":[0.9894458,0.00111523,0.001548608,0.003434723,0.001910963,0.002544692],"domain_scores_gemma":[0.9828427,0.001140497,0.001862944,0.01246341,0.0002132217,0.001477261],"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":[0.000726387,0.0013589,0.0002267753,0.0003106771,0.0002503798,0.01002909,0.000002861935,0.000001008331,0.00007606844,0.00001113165,0.98666,0.0003467274],"study_design_scores_gemma":[0.00232819,0.0005463486,0.004684207,0.0001953965,0.0005313816,0.0003067609,0.0000116441,0.00001414938,0.0000170151,0.0000477249,0.9892069,0.00211031],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000405007,0.0004574984,0.000002133146,0.0003562875,0.00171275,0.002420004,0.9933859,0.0005376613,0.0007228279],"genre_scores_gemma":[0.00005169761,0.0005660731,0.0005472081,0.001843188,0.001620627,0.0008289808,0.9936512,0.0002003234,0.0006906648],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2141822,"threshold_uncertainty_score":0.9999477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05279827150362752,"score_gpt":0.3576545118462875,"score_spread":0.30485624034266,"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."}}