{"id":"W2152586077","doi":"10.5539/elt.v2n4p75","title":"Activating Strategies to Fossilization for English Learners in China","year":2009,"lang":"en","type":"article","venue":"English Language Teaching","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fossilization; China; Psychology; Linguistics; Blocking (statistics); Process (computing); Computer science; History; Philosophy","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":[0.001360759,0.000375386,0.0002158831,0.0006661431,0.002017577,0.001267369,0.0006912698,0.0006336732,0.002314649],"category_scores_gemma":[0.002413164,0.0001642113,0.0001940599,0.0005096083,0.001984103,0.001276481,0.001560709,0.0008767563,0.0001751524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407718,"about_ca_system_score_gemma":0.003174997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008425652,"about_ca_topic_score_gemma":0.01309032,"domain_scores_codex":[0.9992009,0.0003210465,0.00003569262,0.00007369709,0.0001546058,0.0002140375],"domain_scores_gemma":[0.9992977,0.0002456934,0.0001316753,0.0000410463,0.0001168905,0.0001670278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002479716,0.0006402083,0.1537597,0.0005204742,0.00002960809,0.00233255,0.5406435,0.001281465,0.03117051,0.02966912,0.001916185,0.2377886],"study_design_scores_gemma":[0.0001280962,0.0009897865,0.1605776,0.0004425436,0.0001700459,0.002228416,0.6904554,0.007119775,0.03536133,0.02990017,0.07244444,0.000182365],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890911,0.0001886575,0.0009086434,0.0004073362,0.000007370006,0.00002248626,0.000004483925,0.00001418965,0.009355674],"genre_scores_gemma":[0.9947748,0.0003056213,0.001354463,0.00006784116,0.000001931727,0.00002239664,0.00001021346,0.000004702078,0.003457996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008425652,"threshold_uncertainty_score":0.0167532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445958729174453,"score_gpt":0.2749179887711726,"score_spread":0.2604584014794281,"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."}}