{"id":"W4416440159","doi":"10.20383/103.01168","title":"Pol-NIC: an open database on Pollen Nutrients, Imaging and Contaminants","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Pollen; Contamination; Resource (disambiguation); Environmental monitoring","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":[0.0009921904,0.00224431,0.002245226,0.005358752,0.0007675728,0.002832678,0.003558581,0.00317825,0.0339376],"category_scores_gemma":[0.006445543,0.0007606097,0.001705908,0.01002294,0.000433366,0.001747532,0.002444355,0.001575602,0.03795971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001361603,"about_ca_system_score_gemma":0.002336676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01659908,"about_ca_topic_score_gemma":0.02859512,"domain_scores_codex":[0.9988452,0.0001575386,0.0002047703,0.000390886,0.0002735592,0.0001280248],"domain_scores_gemma":[0.997849,0.0008406733,0.000284983,0.0003736575,0.000452873,0.0001987715],"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":[0.0002632096,0.00006151524,0.003969846,0.005869142,0.0002240327,0.0001780216,0.0001059991,0.001488695,0.0008836333,0.001559279,0.9742715,0.0111251],"study_design_scores_gemma":[0.000286692,0.00002827345,0.00739968,0.0007918259,0.0001409638,0.0001704605,0.0001067643,0.0008713633,0.0006308551,0.002416657,0.9870899,0.00006654613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002398338,0.0002436411,0.0001567965,0.00004229033,0.00001386031,0.000009621572,0.9984976,0.0003352961,0.0004610889],"genre_scores_gemma":[0.0004882999,0.0001590199,0.0005454605,0.00004985135,0.000004527489,0.00007047634,0.9984055,0.00005942383,0.0002174434],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0339376,"threshold_uncertainty_score":0.1135326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04572683174197478,"score_gpt":0.3795865899906283,"score_spread":0.3338597582486535,"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."}}