{"id":"W7135356004","doi":"","title":"Constraints in the use of ICT in teaching – Learning processes in secondary schools In Rongai sub county Kajiado count, Kenya","year":2015,"lang":"en","type":"other","venue":"Mount Kenya University E-Repository (Mount Kenya University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information and Communications Technology; Nonprobability sampling; Curriculum; Data collection; Descriptive statistics; Product (mathematics); ICTS","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001060039,0.0003582961,0.0005336915,0.001314384,0.006183465,0.002618302,0.0008965253,0.0006725413,0.004695485],"category_scores_gemma":[0.001823015,0.0007116218,0.0002252773,0.001521186,0.001907542,0.001019522,0.001739452,0.0007701556,0.0003813419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003627916,"about_ca_system_score_gemma":0.007815937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07795817,"about_ca_topic_score_gemma":0.2644309,"domain_scores_codex":[0.9990477,0.0002306452,0.00009430123,0.000123305,0.0001397751,0.0003642548],"domain_scores_gemma":[0.9980894,0.0004369001,0.0005647102,0.00004665221,0.0002029381,0.0006593573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003055624,0.000968254,0.6383381,0.001095928,0.00003602059,0.00766466,0.30824,0.000434663,0.005356018,0.002824371,0.001539172,0.03319721],"study_design_scores_gemma":[0.00002112656,0.0004593099,0.6296481,0.0004654648,0.000041414,0.0007223954,0.3583634,0.0001946245,0.0006540449,0.0001781192,0.009208995,0.00004288286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998752,0.0001233547,0.00001792385,0.0001011741,0.000001623105,0.00003030641,0.00003352726,0.000001552739,0.0009385806],"genre_scores_gemma":[0.9980627,0.0002457394,0.0001632855,0.00005268968,0.000001647353,0.00004552738,0.00004026131,0.00000178312,0.00138635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07795817,"threshold_uncertainty_score":0.1550088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857537528086651,"score_gpt":0.2076689060091703,"score_spread":0.1890935307283038,"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."}}