{"id":"W6906568530","doi":"10.17632/k7zkr5kpzs.1","title":"awake_marmoset_hardware","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Notice; Permission; Documentation; Warranty; Damages; Event (particle physics); Software","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004963112,0.001107279,0.0007314368,0.001123563,0.0003994895,0.001018927,0.001422078,0.00065808,0.06070216],"category_scores_gemma":[0.002034623,0.0004692432,0.0007732862,0.001801918,0.0003308138,0.0007747912,0.000948614,0.0008261939,0.08950552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004574596,"about_ca_system_score_gemma":0.0006595511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007022934,"about_ca_topic_score_gemma":0.01601978,"domain_scores_codex":[0.9996291,0.00006159292,0.00003745142,0.0001558843,0.00006554282,0.00005039904],"domain_scores_gemma":[0.9995344,0.00008528939,0.00005182222,0.000191655,0.00008190233,0.00005496722],"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":[0.0003050052,0.00004501342,0.003437511,0.000888848,0.00007612032,0.00007549726,0.00006041112,0.001085095,0.001148597,0.0009615836,0.9716496,0.02026656],"study_design_scores_gemma":[0.000198447,0.00008460972,0.01570019,0.0002233152,0.000075977,0.0003217147,0.00009672975,0.001445242,0.002240753,0.002512169,0.9770558,0.0000449712],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002352087,0.000277422,0.001150628,0.0001125027,0.00006165078,0.00005350263,0.9872808,0.005258102,0.003453278],"genre_scores_gemma":[0.005016775,0.0001559495,0.001839234,0.0001031787,0.00001316874,0.0002037364,0.9903898,0.0005022592,0.001775815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06070216,"threshold_uncertainty_score":0.203069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03434654097628297,"score_gpt":0.327836798764604,"score_spread":0.293490257788321,"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."}}