{"id":"W6893677333","doi":"10.5281/zenodo.3866852","title":"Megaphyllum montivagum","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; Shore; Habitat; Vegetation (pathology); Distribution (mathematics)","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":[0.0000736447,0.0003961146,0.0002313037,0.001447077,0.000757538,0.0003370747,0.0004682656,0.0004062825,0.01467751],"category_scores_gemma":[0.0002295441,0.0001637208,0.0001877965,0.0006259248,0.0002832764,0.0006242683,0.0009930747,0.000421386,0.005064677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003457081,"about_ca_system_score_gemma":0.0001819289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003387187,"about_ca_topic_score_gemma":0.004944269,"domain_scores_codex":[0.9998938,0.00001638681,0.000008247322,0.00002856907,0.00002596602,0.00002707183],"domain_scores_gemma":[0.9999136,0.00001200992,0.00003485798,0.000009822519,0.00001901465,0.00001067881],"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":[0.0003533795,0.00009941543,0.04164338,0.0007790762,0.00007884684,0.001196639,0.001819096,0.0004350142,0.1014592,0.01071218,0.017343,0.8240808],"study_design_scores_gemma":[0.0000279705,0.000197344,0.314108,0.0003874616,0.00006646671,0.003972961,0.0008181219,0.0005648469,0.004840784,0.001612538,0.6733801,0.00002343361],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3370141,0.02994307,0.008288327,0.0009842513,0.000422864,0.0003458806,0.00558763,0.001454238,0.6159597],"genre_scores_gemma":[0.9541121,0.003827369,0.006399139,0.0004570494,0.0001872152,0.0001922397,0.005879078,0.00009121859,0.02885457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01467751,"threshold_uncertainty_score":0.04910111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04039396246919327,"score_gpt":0.2728774325420639,"score_spread":0.2324834700728707,"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."}}