{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006396591,0.002080734,0.001263653,0.003116645,0.0007110569,0.001408238,0.002429202,0.001613489,0.02256707],"category_scores_gemma":[0.002401812,0.0004485126,0.001129071,0.004550285,0.0003293514,0.0008132709,0.001354289,0.001641474,0.03710185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008322241,"about_ca_system_score_gemma":0.001492041,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02200446,"about_ca_topic_score_gemma":0.04600488,"domain_scores_codex":[0.9993539,0.00007963615,0.00005070022,0.0001934558,0.0002363147,0.00008588479],"domain_scores_gemma":[0.9990792,0.0001489038,0.00007589857,0.0002358445,0.0003436885,0.0001164709],"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":[0.00008393165,0.0000382692,0.001631191,0.0004173387,0.00005418476,0.00004847355,0.00002985511,0.0007495486,0.0003553454,0.0003601707,0.9918933,0.004338562],"study_design_scores_gemma":[0.0003607841,0.00002794297,0.01796634,0.0001894691,0.00005315919,0.0001647694,0.0001054205,0.002256053,0.0008589054,0.001035488,0.9769403,0.00004148607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001092338,0.0001165755,0.0001410353,0.00004143189,0.00003409485,0.00001694215,0.9969325,0.000769589,0.0008553889],"genre_scores_gemma":[0.0006978629,0.00002822811,0.0002808171,0.00001409407,0.000005306064,0.00003152712,0.9985455,0.00006170891,0.0003349028],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9779955,"threshold_uncertainty_score":0.07549435,"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."}}