{"id":"W1908204048","doi":"10.14742/ajet.1319","title":"Contrasting syntactic and semantic units in the analysis of online discussions","year":2005,"lang":"en","type":"article","venue":"Australasian Journal of Educational Technology","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Paragraph; Natural language processing; Coding (social sciences); Identifiability; Asynchronous communication; Artificial intelligence; Information retrieval; Statistics; World Wide Web; Machine learning; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02593363,0.0005281533,0.0006227671,0.01060242,0.001878264,0.005797019,0.001327797,0.0009254558,0.001852655],"category_scores_gemma":[0.1778296,0.0005896498,0.0008298308,0.006679727,0.005108305,0.007018453,0.004345277,0.001193657,0.0004131219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001969463,"about_ca_system_score_gemma":0.00191409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001473191,"about_ca_topic_score_gemma":0.001638277,"domain_scores_codex":[0.9443674,0.04241042,0.002705939,0.002219395,0.007347056,0.0009497977],"domain_scores_gemma":[0.7016532,0.2615194,0.01503976,0.006555654,0.01449213,0.0007398741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00185032,0.000430956,0.1417636,0.002449628,0.0003220625,0.0008242827,0.4439306,0.00156275,0.02940041,0.04046997,0.001140368,0.3358551],"study_design_scores_gemma":[0.0001856101,0.001281415,0.3750101,0.002013756,0.0005862775,0.00151176,0.3780774,0.03710335,0.06862166,0.1186217,0.01645172,0.0005353411],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9091888,0.0004691777,0.0775991,0.0003206959,0.00008174808,0.000412229,0.000127815,0.0002179147,0.01158254],"genre_scores_gemma":[0.9517136,0.0001760628,0.04656906,0.00007351339,0.00003595854,0.0006598669,0.000146538,0.0001180401,0.0005075205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02593363,"threshold_uncertainty_score":0.1371518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374726659945562,"score_gpt":0.3580771284903245,"score_spread":0.3343298618908688,"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."}}