{"id":"W6889015751","doi":"10.25345/c5j52z","title":"MassIVE MSV000087525 - MAGEL2- Full length and truncation Interactome","year":2021,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Truncation (statistics); Interactome; Generalization; Term (time)","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":[0.0008698762,0.00342152,0.003028282,0.005576603,0.00177848,0.002974734,0.00346934,0.003280228,0.08881917],"category_scores_gemma":[0.004321227,0.0009269578,0.002249943,0.007894198,0.000523589,0.001137817,0.002661072,0.001623014,0.080711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001397159,"about_ca_system_score_gemma":0.003456058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02513626,"about_ca_topic_score_gemma":0.05421743,"domain_scores_codex":[0.9989794,0.000111875,0.00007824988,0.0003696771,0.0002500471,0.0002106954],"domain_scores_gemma":[0.998701,0.0004287701,0.0001167883,0.0002697768,0.000264573,0.0002191321],"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":[0.0002742225,0.00003039055,0.001613829,0.001589228,0.0001702149,0.0001141722,0.00005038501,0.0004940619,0.0009508867,0.0006988044,0.9910623,0.002951554],"study_design_scores_gemma":[0.0008627921,0.00006877778,0.0101833,0.0007356028,0.0004663114,0.0004187409,0.0001333666,0.001598047,0.002170024,0.003196527,0.980076,0.00009044274],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005598289,0.0004651912,0.0001369919,0.00007225737,0.00004180465,0.00001428708,0.9963459,0.0008876637,0.001476128],"genre_scores_gemma":[0.001124577,0.0001906907,0.0004476848,0.00009002096,0.000009490258,0.0000734168,0.9970936,0.0001445404,0.0008260485],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08881917,"threshold_uncertainty_score":0.2971298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551385721205748,"score_gpt":0.2769528868199961,"score_spread":0.2614390296079386,"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."}}