{"id":"W6977842810","doi":"10.7910/dvn/8qpl75/wbz4qi","title":"qik20120509_03.txt.gz","year":2021,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001919431,0.003720271,0.003288266,0.005306549,0.001824922,0.005924112,0.006270078,0.004835675,0.3475682],"category_scores_gemma":[0.01411099,0.001571646,0.002354905,0.00984728,0.0010205,0.003166175,0.0048211,0.002907654,0.3528999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00275087,"about_ca_system_score_gemma":0.003848643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03187221,"about_ca_topic_score_gemma":0.04805587,"domain_scores_codex":[0.9983836,0.0003417698,0.0001588713,0.0005323566,0.000266837,0.0003165285],"domain_scores_gemma":[0.9956749,0.001639596,0.0003469782,0.0009319792,0.0009112908,0.0004952273],"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":[0.00005327063,0.0000106691,0.0002949524,0.001044509,0.00003608874,0.0000108476,0.00002268374,0.0001491789,0.00006114274,0.0004532164,0.9971258,0.0007377038],"study_design_scores_gemma":[0.0005816182,0.00002653454,0.00182998,0.0006279033,0.00006121641,0.00004212381,0.00008241097,0.0003303066,0.0002876093,0.00296728,0.9931101,0.000053081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002973617,0.00006356592,0.00003468103,0.00008209583,0.0000227331,0.000006850777,0.9988354,0.0004030084,0.0005220507],"genre_scores_gemma":[0.0002526904,0.00007312728,0.0001641837,0.0001185624,0.0000129933,0.00008308706,0.998316,0.0002422466,0.0007370599],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6524318,"threshold_uncertainty_score":0.9306148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195836167539267,"score_gpt":0.2598322243340834,"score_spread":0.2378738626586908,"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."}}