{"id":"W1978943703","doi":"10.4018/jnmc.2011040101","title":"Understanding Advances in Nanotechnology","year":2011,"lang":"en","type":"article","venue":"International Journal of Nanotechnology and Molecular Computation","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Nanotechnology; Realm; Predictability; Applications of nanotechnology; Societal impact of nanotechnology; Corporate governance; Focus (optics); Computer science; Engineering; Materials science; Political science; Management; Physics; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002260303,0.00006697288,0.0001232452,0.0003510721,0.00003151628,0.00001505119,0.0002319375,0.0001061469,0.00001935812],"category_scores_gemma":[0.00007236633,0.00006213983,0.00002953438,0.0001280179,0.0001429803,0.0002054926,0.00005216374,0.0001139431,0.000005678926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006075417,"about_ca_system_score_gemma":0.00002528344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004781213,"about_ca_topic_score_gemma":0.000008084874,"domain_scores_codex":[0.9992916,0.00003334936,0.0003145512,0.0001181386,0.0001383422,0.0001039994],"domain_scores_gemma":[0.9995385,0.00003983091,0.0002406802,0.00005684693,0.0001027041,0.00002145775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006083596,0.00008987466,0.0007625702,0.000003172861,0.0000130884,0.0001030901,0.0001705352,0.0002405033,0.8688203,0.1096319,0.000007807524,0.02009635],"study_design_scores_gemma":[0.0005401248,0.0001173917,0.0004052206,0.00005387826,0.0000107136,0.0002723226,0.0002753549,0.0004645513,0.8126608,0.1846892,0.0004231722,0.00008726912],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7055702,0.0006315583,0.2925421,0.0009074851,0.0001818882,0.00004158854,0.000001095582,0.00002011603,0.000103935],"genre_scores_gemma":[0.9875769,0.0002600396,0.01206238,0.00007800543,0.00001193368,0.000003714477,5.389311e-7,0.00000532209,0.0000011842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2820067,"threshold_uncertainty_score":0.2533989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04201803001457306,"score_gpt":0.2814259117510412,"score_spread":0.2394078817364682,"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."}}