{"id":"W4393555852","doi":"10.5281/zenodo.2530388","title":"Multi_Level_Biological_Networks","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science","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":[0.001765145,0.001295467,0.0006849366,0.006770585,0.001531228,0.003543253,0.001331542,0.0008667302,0.01896614],"category_scores_gemma":[0.007036333,0.0007153064,0.002689382,0.006008927,0.000558784,0.005994482,0.003458285,0.001325726,0.006471634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001618129,"about_ca_system_score_gemma":0.001684923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007884685,"about_ca_topic_score_gemma":0.0115055,"domain_scores_codex":[0.9977964,0.0004753111,0.000227779,0.0008217755,0.0005427038,0.000136029],"domain_scores_gemma":[0.9973917,0.001209663,0.0002705359,0.0005404305,0.0004445393,0.0001431239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005689465,0.0001658917,0.03547246,0.007187382,0.001239397,0.001223202,0.001830276,0.05126354,0.01234686,0.2837528,0.218704,0.3862451],"study_design_scores_gemma":[0.00003441799,0.00005100113,0.01096376,0.0007961062,0.0004731487,0.0005577793,0.0004423654,0.07595859,0.006227584,0.1733496,0.7310246,0.000121018],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.0270443,0.006448855,0.6148983,0.003600604,0.0007334204,0.0009053848,0.2703265,0.0249814,0.05106122],"genre_scores_gemma":[0.1887515,0.007230154,0.4304623,0.001431917,0.0003469904,0.001938501,0.3469679,0.002736588,0.02013414],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01896614,"threshold_uncertainty_score":0.06344807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02828450056463196,"score_gpt":0.2708575708777236,"score_spread":0.2425730703130916,"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."}}