{"id":"W6926963593","doi":"10.25666/dataosu-2017-07-19-04","title":"Pollen analysis - Montréal-la-Cluse (F-01), A404 derrière la côte du château","year":2021,"lang":"en","type":"dataset","venue":"Université de Bourgogne-Franche-Comté (UBFC)","topic":"Marine Toxins and Detection Methods","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pollen; Palynology; Feature (linguistics); Vegetation (pathology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001299839,0.0009246389,0.001273544,0.000719471,0.000956514,0.0002126981,0.001396325,0.001038184,0.03908012],"category_scores_gemma":[0.0002366593,0.0009964949,0.00113987,0.002287266,0.0004566725,0.0003077208,0.002441665,0.001162532,0.0008465094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613608,"about_ca_system_score_gemma":0.0001661032,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03401077,"about_ca_topic_score_gemma":0.0217704,"domain_scores_codex":[0.9946613,0.001214637,0.0006367095,0.001484713,0.0009831106,0.001019573],"domain_scores_gemma":[0.9961513,0.0005936366,0.0005584101,0.001902504,0.00004665419,0.0007475524],"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":[0.0001675366,0.0002473556,0.0053844,0.00006459878,0.0009462478,0.001551229,0.0004450947,0.001628108,0.0001623137,0.0000165628,0.9850147,0.004371859],"study_design_scores_gemma":[0.001354536,0.00006766825,0.01319983,0.00003823475,0.00207128,0.0002021428,0.0003511761,0.0009035039,0.0001620752,0.0001004978,0.9805027,0.001046377],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03124028,0.001556174,0.00423621,0.00148251,0.0009289524,0.00102783,0.8687609,0.0005347915,0.09023236],"genre_scores_gemma":[0.009379266,0.009775496,0.0126937,0.002949061,0.001196939,0.00006863177,0.8593227,0.0003788456,0.1042354],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03823361,"threshold_uncertainty_score":0.9999315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002882689449690212,"score_gpt":0.1941408862502952,"score_spread":0.191258196800605,"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."}}