{"id":"W2952166899","doi":"","title":"Mapping of Research Productivity on Nanotechnology in Canada: A Scientometric Profile","year":2019,"lang":"en","type":"article","venue":"Lincoln (University of Nebraska)","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Scientometrics; Geography; Bibliometrics; Regional science; Data science; Nanotechnology; Library science; Computer science; Economics; Economic growth; Materials science","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":["metaresearch","bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.0191511,0.0001059308,0.0004724622,0.1394115,0.0001614222,0.00007048371,0.003047386,0.0001444316,0.0007309463],"category_scores_gemma":[0.0143154,0.0001022081,0.00008752223,0.3777037,0.0004257406,0.0003683976,0.001350003,0.0005672887,0.0001906746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009244208,"about_ca_system_score_gemma":0.003219308,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4066465,"about_ca_topic_score_gemma":0.2860923,"domain_scores_codex":[0.9887937,0.0004035801,0.0003838229,0.000886204,0.008865375,0.0006673089],"domain_scores_gemma":[0.9916193,0.003857074,0.0003190343,0.001049947,0.002962038,0.0001925512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001396929,0.0004283178,0.8612915,0.0000639261,0.00001580239,0.00005084039,0.0004170301,0.0002742711,0.007892502,0.001689739,0.00490258,0.1228338],"study_design_scores_gemma":[0.001002162,0.0004474257,0.9672489,0.00006037985,0.000001291538,0.000002622586,0.008726242,0.005300002,0.003731018,0.001738711,0.01157516,0.0001661288],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898255,0.0001309219,0.000110658,0.001549043,0.0002880659,0.0006053278,0.00004105403,0.000009398097,0.007440065],"genre_scores_gemma":[0.9942814,0.00003072323,0.0007655341,0.0000103103,0.00001193125,6.472696e-7,0.000001494928,0.000005397359,0.004892574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2382922,"threshold_uncertainty_score":0.9939874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4355775233680524,"score_gpt":0.4775579212335161,"score_spread":0.0419803978654637,"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."}}