{"id":"W4386375411","doi":"10.31399/asm.amp.2017-08.p016","title":"Using Induction Melting to Make Lithium-Ion Battery Material","year":2017,"lang":"en","type":"article","venue":"AM&P Technical Articles","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Western University; Polytechnique Montréal; Natural Resources Canada","funders":"","keywords":"Battery (electricity); Materials science; Homogeneous; Casting; Lithium (medication); Process (computing); Lithium-ion battery; Cathode; Process engineering; Ion; Computer science; Metallurgy; Electrical engineering; Chemistry; Engineering; Thermodynamics","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":[0.0002482221,0.0001659441,0.0001972609,0.00006324262,0.0002665042,0.000245736,0.0003110059,0.00009645212,0.0001552765],"category_scores_gemma":[0.0001130689,0.0001654977,0.00002749372,0.00005550031,0.00007182986,0.00038342,0.0001938558,0.0001021417,0.0001326615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009974762,"about_ca_system_score_gemma":0.000004128121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002256352,"about_ca_topic_score_gemma":0.000008231292,"domain_scores_codex":[0.9988655,0.00002427321,0.00034403,0.0002365395,0.0001755802,0.0003540907],"domain_scores_gemma":[0.9991979,0.00002302116,0.00007128151,0.0005948032,0.00002578733,0.00008718504],"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":[0.00001782372,0.00001662094,0.0008309229,0.00002252593,0.000007920056,0.000006160056,0.00003994906,0.001527814,0.9871633,0.00009712606,0.0002503053,0.01001951],"study_design_scores_gemma":[0.0001746804,0.00003524913,0.01340545,0.00009231836,0.00001640417,0.00002269064,0.00002175924,0.0004856211,0.9826439,0.001628431,0.001213438,0.0002600398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872912,0.000006025668,0.009775428,0.0003585715,0.001415168,0.0002104982,0.00001164318,0.0005288174,0.0004026521],"genre_scores_gemma":[0.9784773,0.000003772273,0.02074376,0.000152536,0.0005214831,0.00002955118,0.000002651786,0.00004725101,0.00002168614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01257453,"threshold_uncertainty_score":0.6748801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05008221825474939,"score_gpt":0.3061327315764251,"score_spread":0.2560505133216757,"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."}}