{"id":"W6950115882","doi":"10.5281/zenodo.3867113","title":"Cylindroiulus londinensis","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada)","funders":"","keywords":"Woodland; Habitat; Evergreen; Range (aeronautics); Distribution (mathematics); Wetland","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":[0.0001086931,0.0004976407,0.0002639156,0.001135813,0.0007054665,0.0003009588,0.000395526,0.0003705888,0.01845535],"category_scores_gemma":[0.0002753836,0.0001116621,0.0001330253,0.0005909678,0.0003320799,0.0005990281,0.0005844624,0.0001920414,0.007407994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006038676,"about_ca_system_score_gemma":0.0001968232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004757168,"about_ca_topic_score_gemma":0.01296929,"domain_scores_codex":[0.9998702,0.00001499214,0.00001987401,0.00004452826,0.00003706056,0.00001331974],"domain_scores_gemma":[0.9998605,0.00001679038,0.00005628373,0.000009412433,0.000039443,0.00001750656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007707361,0.0001093705,0.092179,0.001848974,0.00008036265,0.002529256,0.001274335,0.0008940547,0.06116777,0.002969355,0.03373871,0.8024381],"study_design_scores_gemma":[0.00007297893,0.0005321164,0.5082625,0.0004623381,0.00008271095,0.007100258,0.001441561,0.0005474272,0.003996381,0.0005502213,0.4769157,0.00003579651],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3846996,0.02021104,0.004765085,0.0006637129,0.0007633845,0.0003837235,0.007003307,0.0007828923,0.5807272],"genre_scores_gemma":[0.925518,0.003833731,0.00279641,0.0006066346,0.0002193955,0.0002137268,0.006210703,0.00002578439,0.06057556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01845535,"threshold_uncertainty_score":0.06173933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04326596248763605,"score_gpt":0.2789599096256608,"score_spread":0.2356939471380248,"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."}}