{"id":"W4398688303","doi":"10.7910/dvn/0o6vrk/kbig0a","title":"claims_per_patents_ctry_ep_Canada-1.png","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Metallurgy and Material Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Genealogy; History","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007496102,0.0004314816,0.0005423843,0.0001384299,0.0002060569,0.0003338789,0.001920232,0.0003495576,0.3504249],"category_scores_gemma":[0.0001496318,0.0003754152,0.0001130261,0.0001710537,0.0002012379,0.0006000649,0.0008143216,0.0002936298,0.6566539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001115849,"about_ca_system_score_gemma":0.000351492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001946728,"about_ca_topic_score_gemma":0.0004261887,"domain_scores_codex":[0.9969134,0.000160402,0.0004696713,0.0009432997,0.0008073827,0.0007058672],"domain_scores_gemma":[0.9971676,0.00005531477,0.0003200349,0.002106263,0.00006909433,0.0002816779],"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":[0.00003408456,0.00004085036,7.489043e-7,0.0001240747,0.00001088237,0.0001009164,0.000005660306,0.00001026804,0.02403191,0.00003881228,0.9755678,0.00003397401],"study_design_scores_gemma":[0.0002431953,0.00004988921,0.00001396926,0.00007094894,0.00007119808,0.00002809974,0.00001434395,0.000007307623,0.002591939,0.00002696863,0.9963945,0.0004876845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006620439,0.000001241197,0.00002538262,0.000006319313,0.007341642,0.0003321352,0.9909687,0.00005955083,0.0006030042],"genre_scores_gemma":[0.00007603507,0.0001252893,0.0002519421,0.0007380329,0.0003889888,0.00002415857,0.9962236,0.00002182248,0.002150111],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.306229,"threshold_uncertainty_score":0.9998698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820543550770179,"score_gpt":0.2495473862126127,"score_spread":0.2213419507049109,"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."}}