{"id":"W4398870430","doi":"10.7910/dvn/tlahpx/6e8qbf","title":"ddAle_Ott_20191019_06928500.mat","year":2020,"lang":"fr","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["insufficient_payload"],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001174294,0.003008572,0.002125286,0.005322596,0.001359073,0.004606477,0.003784857,0.003061591,0.3627099],"category_scores_gemma":[0.00892078,0.001050846,0.001431362,0.007893822,0.0007616948,0.0027502,0.003120281,0.002041294,0.4085999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002320424,"about_ca_system_score_gemma":0.002581367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04052437,"about_ca_topic_score_gemma":0.05419309,"domain_scores_codex":[0.9988428,0.000180182,0.00009784496,0.0003855894,0.0002282803,0.0002652513],"domain_scores_gemma":[0.9968703,0.0009215379,0.0002743405,0.000772931,0.0007783534,0.0003824828],"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":[0.00002454127,0.000004492964,0.0001452111,0.0002630253,0.0000101188,0.000004953212,0.00000874844,0.00008159916,0.00002697748,0.0003144001,0.9984829,0.0006330934],"study_design_scores_gemma":[0.0001909981,0.00001182629,0.001250826,0.0002770311,0.00001811958,0.00002150852,0.00005135284,0.0002239838,0.000177139,0.001498337,0.9962483,0.00003072741],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002178089,0.00003810185,0.00002220883,0.00006592746,0.0000231848,0.000002610978,0.9987788,0.0003674175,0.0006799153],"genre_scores_gemma":[0.0002487796,0.00005961698,0.0001326588,0.00008268793,0.00001624702,0.00003324526,0.998017,0.0002434449,0.001166348],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6372901,"threshold_uncertainty_score":0.9090169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02450593959360857,"score_gpt":0.2503224828680015,"score_spread":0.2258165432743929,"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."}}