{"id":"W4319878649","doi":"10.1016/j.mseb.2023.116332","title":"Silicon-Germanium and carbon-based superconductors for electronic, industrial, and medical applications","year":2023,"lang":"en","type":"article","venue":"Materials Science and Engineering B","topic":"Inorganic Chemistry and Materials","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Superconductivity; Germanium; Engineering physics; Commercialization; Condensed matter physics; Materials science; Physics; Nanotechnology; Silicon; Metallurgy; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0001607169,0.0002044018,0.0001503012,0.0004095751,0.0002177139,0.0003838706,0.0002648906,0.0004517227,0.002725715],"category_scores_gemma":[0.0001467742,0.00007693864,0.0001717535,0.0003677468,0.0003646285,0.0002813372,0.0003868105,0.0002555236,0.0004759215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002723405,"about_ca_system_score_gemma":0.0002961959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003120971,"about_ca_topic_score_gemma":0.001371695,"domain_scores_codex":[0.9999131,0.00001147856,0.000005385785,0.00001197413,0.00004040749,0.00001770065],"domain_scores_gemma":[0.9999477,0.00001101991,0.00000679189,0.000005051061,0.00001368368,0.00001572207],"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":[0.0004849449,0.0001022704,0.001906796,0.001166029,0.00007074015,0.0006491852,0.0001066933,0.001443195,0.8068093,0.08399151,0.0121739,0.09109543],"study_design_scores_gemma":[0.0001163207,0.001178743,0.006137045,0.0001934753,0.0001007782,0.001534714,0.0002636039,0.006871972,0.7648184,0.01920253,0.1995329,0.00004947423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7134936,0.1591166,0.01772423,0.004441019,0.002315906,0.0001212536,0.001033569,0.0003879546,0.1013659],"genre_scores_gemma":[0.9630151,0.01659007,0.007753256,0.0002868932,0.00020233,0.00002151635,0.0004241742,0.00002015382,0.0116866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002725715,"threshold_uncertainty_score":0.009118438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307953173510662,"score_gpt":0.2262679347481975,"score_spread":0.2131884030130909,"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."}}