{"id":"W4398277149","doi":"10.7910/dvn/pkjufn/jmmhtn","title":"FCC2001.160.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Ran; Biology; Cell biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005762594,0.0003756368,0.0004969864,0.0001596459,0.00004282046,0.00003580002,0.0007087286,0.000536427,0.01276286],"category_scores_gemma":[0.00002177555,0.0003964825,0.000116974,0.0001850631,0.00005240498,0.0001159999,0.00009062597,0.0006608629,0.2812438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005198276,"about_ca_system_score_gemma":0.0000289523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001627134,"about_ca_topic_score_gemma":0.0002712315,"domain_scores_codex":[0.998696,0.0000125594,0.0003579989,0.0003719573,0.0001997158,0.0003617481],"domain_scores_gemma":[0.99861,0.00001925487,0.00005533046,0.001150025,0.00001602177,0.0001494334],"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":[0.000005024523,0.00001136481,0.000002566248,0.0004476625,0.0001128848,0.0004014724,0.000008601852,0.00005119122,0.00004284632,0.00003571509,0.9986424,0.0002382087],"study_design_scores_gemma":[0.0002688975,0.00002248795,0.00001786992,0.00006963241,0.00009675867,0.00002799419,0.00001631334,0.00006981517,0.00002842398,0.000009219786,0.9989766,0.000395938],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009271113,0.000004740552,0.0001642233,0.000004318541,0.001380731,0.0002125948,0.9969152,0.0008514626,0.0004574146],"genre_scores_gemma":[0.0001361982,0.0005120258,0.000160094,0.00009682815,0.0003325083,0.00003169589,0.9986004,0.00005807475,0.00007215873],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.268481,"threshold_uncertainty_score":0.9998487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028644552546442,"score_gpt":0.1922603851564491,"score_spread":0.1819739396309847,"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."}}