{"id":"W2052303388","doi":"10.1002/bmb.17","title":"Commentary: Just in time learning with radio frequency identification devices (RFIDs)","year":2007,"lang":"en","type":"article","venue":"Biochemistry and Molecular Biology Education","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radio-frequency identification; Identification (biology); Computer science; Key (lock); Telecommunications; Control (management); Set (abstract data type); Multimedia; Computer security; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001561777,0.000108789,0.00007873101,0.0000597713,0.00003418947,0.00001602045,0.00007430718,0.00009985083,0.000009884712],"category_scores_gemma":[0.0000160557,0.0001179654,0.00001108904,0.0001116183,0.00004135144,0.00004053494,0.00001184423,0.0001555087,0.000004988545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009047815,"about_ca_system_score_gemma":0.00001501797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002173187,"about_ca_topic_score_gemma":0.000001796715,"domain_scores_codex":[0.9994918,0.00001460181,0.0001389856,0.000162232,0.00004079082,0.0001516327],"domain_scores_gemma":[0.9997906,0.00001764741,0.00002895814,0.0001018684,0.0000148008,0.00004613151],"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":[0.000004208419,0.00002409402,0.02115924,0.00004357907,0.000014189,0.000001643379,0.0001329098,0.000411932,0.9769791,0.00005211873,0.00005860722,0.001118432],"study_design_scores_gemma":[0.0001751953,0.00003013247,0.008939351,0.00006178022,0.00001116109,0.00002429531,0.0003758955,0.0004743067,0.9880879,0.00002279808,0.001591462,0.0002057131],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992568,0.001853307,0.004408757,0.000112748,0.00008949908,0.00007893671,9.204238e-7,0.00009071193,0.0007971423],"genre_scores_gemma":[0.9971694,0.00002524314,0.002368089,0.00009874093,0.00005211089,0.00001781216,0.0001997117,0.00001737986,0.00005154136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01221988,"threshold_uncertainty_score":0.4810491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002767266157585346,"score_gpt":0.2369392001185711,"score_spread":0.2341719339609858,"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."}}