{"id":"W6968143779","doi":"10.5281/zenodo.14040810","title":"Damzenia V. Alekseev","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Linguistic and Cultural Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Saskatchewan Museum; University of Regina","funders":"","keywords":"Process (computing); Population; Algae","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":[0.0002263498,0.0006883056,0.0004807264,0.002351674,0.001516425,0.0009184105,0.0006597218,0.0005817115,0.01135899],"category_scores_gemma":[0.0006464935,0.0002438907,0.0002871052,0.0009562506,0.0008758757,0.001671134,0.001739099,0.001156687,0.002886526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008020626,"about_ca_system_score_gemma":0.00060912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005113428,"about_ca_topic_score_gemma":0.00563832,"domain_scores_codex":[0.9996111,0.00002802461,0.00003566705,0.0001488622,0.0001200749,0.00005628729],"domain_scores_gemma":[0.9998268,0.0000345161,0.00006181563,0.0000256263,0.00003282483,0.00001840379],"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":[0.000736139,0.0001318399,0.01152114,0.001801345,0.000190181,0.001911899,0.002579233,0.003413187,0.05977125,0.05914858,0.04910545,0.8096898],"study_design_scores_gemma":[0.000101903,0.0001052951,0.07895307,0.0006796253,0.0002367844,0.003907301,0.000886462,0.001088074,0.007825123,0.01268297,0.8934612,0.00007213654],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2356249,0.03847696,0.02690989,0.002577589,0.004464958,0.0006341262,0.0111624,0.002546216,0.6776029],"genre_scores_gemma":[0.9107687,0.006349149,0.01170407,0.00118181,0.0006859206,0.0001684262,0.004415392,0.0001997238,0.06452668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01135899,"threshold_uncertainty_score":0.03799969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04096347564760775,"score_gpt":0.2306287460277002,"score_spread":0.1896652703800925,"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."}}