{"id":"W6964454414","doi":"10.25345/c5dv5r","title":"MassIVE MSV000087430 - Rosenthal_Zebrafish_TurboID_P88_SAINT5429_miniTurbo_transgenics_2021","year":2021,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"","keywords":"Identification (biology); Process (computing); Work (physics); Set (abstract data type)","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":[0.001436405,0.003202392,0.00197532,0.005300195,0.001627775,0.002975299,0.004028254,0.003280379,0.2833818],"category_scores_gemma":[0.008576561,0.001225686,0.001869199,0.006245345,0.0006624407,0.001480495,0.002612378,0.001642293,0.2346391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001755915,"about_ca_system_score_gemma":0.004022709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03469149,"about_ca_topic_score_gemma":0.06939319,"domain_scores_codex":[0.9987723,0.0001528852,0.00009790376,0.0003952983,0.0003170878,0.0002645737],"domain_scores_gemma":[0.9967663,0.001320155,0.0002820207,0.000571831,0.0006825459,0.0003772124],"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":[0.00008929038,0.00001459299,0.0007645118,0.0008041225,0.00004109307,0.00002038257,0.00002981194,0.0002168733,0.0001827046,0.0005273552,0.9953306,0.001978693],"study_design_scores_gemma":[0.0005025075,0.00002861705,0.004068696,0.0005206257,0.00009895067,0.00006310192,0.00008296063,0.0005185935,0.0007540879,0.002700706,0.9906002,0.00006075819],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006983826,0.00004732605,0.00007436662,0.00004236652,0.00001715367,0.000007418843,0.9982885,0.0006458152,0.0008072678],"genre_scores_gemma":[0.0003880635,0.00005476034,0.0004496655,0.00008921311,0.000006836375,0.00007975937,0.9973699,0.0003950291,0.00116677],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2833818,"threshold_uncertainty_score":0.9480065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02043051747527171,"score_gpt":0.2666267695996262,"score_spread":0.2461962521243545,"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."}}