{"id":"W2092391432","doi":"10.5539/mas.v5n5p227","title":"Analysis of Information Literacy Education Strategies for College Students Majoring in Science and Engineering","year":2011,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information literacy; Curriculum; Scientific literacy; Science and engineering; Lifelong learning; Mathematics education; Field (mathematics); Literacy; Computer science; Science education; Engineering ethics; Pedagogy; Engineering; Sociology; Psychology; Library science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008850339,0.000272775,0.0003667845,0.001878833,0.00071088,0.001487644,0.0004875821,0.0005802742,0.004076564],"category_scores_gemma":[0.009686152,0.0001743055,0.0005775174,0.001211863,0.0003296878,0.001169613,0.0007531834,0.0006057833,0.0006858913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161226,"about_ca_system_score_gemma":0.001710836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005961504,"about_ca_topic_score_gemma":0.008091173,"domain_scores_codex":[0.9994417,0.0001277998,0.0000635623,0.00006019818,0.0001472002,0.0001596884],"domain_scores_gemma":[0.9951968,0.002314735,0.0007255066,0.0001299713,0.0007826461,0.0008503755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007746831,0.006521355,0.8057118,0.0001989143,0.00010434,0.0002972954,0.03200459,0.0002273081,0.001561279,0.0007222621,0.0009443167,0.1509319],"study_design_scores_gemma":[0.00007763205,0.001796801,0.9606048,0.00008898369,0.0001067184,0.0001417457,0.03257782,0.001229491,0.0009505126,0.0003931289,0.002002334,0.00003006904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988716,0.00004375919,0.00004108491,0.00004552897,0.000001895183,0.00003700257,0.00002722989,0.00000314333,0.0009286279],"genre_scores_gemma":[0.9985966,0.00008690364,0.0001375328,0.00003130208,0.000001735892,0.00005278594,0.0001055145,0.000002179415,0.0009853443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005961504,"threshold_uncertainty_score":0.01363748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574050953873448,"score_gpt":0.2963849523375817,"score_spread":0.2806444427988473,"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."}}