{"id":"W6926064083","doi":"10.21233/n3zq80","title":"Lac Louis pollen dataset","year":2017,"lang":"en","type":"dataset","venue":"Neotoma Paleoecological Database","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Pollen; Assemblage (archaeology); Table (database); Phenology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006608306,0.001187912,0.000702653,0.002711823,0.0006049132,0.001569249,0.001659911,0.001255434,0.0363758],"category_scores_gemma":[0.003443972,0.0003331015,0.0008266234,0.003761016,0.0002887677,0.0007846727,0.001402715,0.001345147,0.04812941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008920625,"about_ca_system_score_gemma":0.001802384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01337983,"about_ca_topic_score_gemma":0.0347129,"domain_scores_codex":[0.9995074,0.00007030964,0.00004812052,0.0001499601,0.0001584494,0.00006573934],"domain_scores_gemma":[0.9988801,0.0003055445,0.0001033446,0.0002440405,0.0003501334,0.0001169006],"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":[0.00009354958,0.0000324277,0.001967287,0.0004882305,0.00005522347,0.00005116794,0.00003417269,0.0005934866,0.0005537322,0.0007853481,0.9899558,0.005389548],"study_design_scores_gemma":[0.0002129702,0.00001552081,0.00634412,0.0001474358,0.00003279707,0.00006448854,0.00006455924,0.000966177,0.0006291767,0.0009964994,0.990504,0.00002216952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007377319,0.00007110753,0.0001409483,0.00004334392,0.00001866967,0.00001036587,0.9974453,0.0007019951,0.0008304726],"genre_scores_gemma":[0.0006653084,0.00002849902,0.0003234363,0.00002602039,0.000004134363,0.00004087177,0.9983574,0.00009024206,0.000464045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0363758,"threshold_uncertainty_score":0.1216891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02573800130060465,"score_gpt":0.3020086824278549,"score_spread":0.2762706811272502,"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."}}